FLT3 signalling pathways in Acute Myeloid Leukaemia

A thesis submitted to the University of Manchester for the degree of

Doctor of Medicine

In the Faculty of Biology, Medicine and Health

2019 Claudia M. Gorcea

School of Medicine

CONTENTS

CONTENTS...... 2 LIST OF FIGURES ...... 4 LIST OF TABLES ...... 6 ABBREVIATIONS ...... 7 DECLARATION...... 9 COPYRIGHT STATEMENT ...... 9 ACKNOWLEDGEMENT ...... 10 ABSTRACT ...... 11 1 INTRODUCTION ...... 12

1.1 ACUTE MYELOID LEUKAEMIA (AML) ...... 12 1.1.1 Introduction ...... 12 1.1.2 Pathogenesis ...... 12 1.1.3 Clinical presentation and diagnosis ...... 13 1.1.4 Classification ...... 14 1.1.5 Prognostic factors and groups ...... 15 1.1.6 Treatment ...... 18 1.2 FLT3 MUTATIONS ...... 22 1.2.1 Introduction ...... 22 1.2.2 Types of Mutations ...... 23 1.2.3 Signalling pathways through FLT3 ...... 26 1.2.4 FLT3 mechanism of action ...... 29 1.2.5 FL background ...... 30 1.2.6 FLT3 and impact on AML behaviour ...... 32 1.3 FLT3 TKIS OVERVIEW ...... 33 1.3.1 History ...... 33 1.3.2 Clinical trials of FLT3 TKIs in monotherapy ...... 35 1.3.3 FLT3-TKIs in combination with chemotherapy ...... 39 1.3.4 FLT3-TKIs in combination with other small molecules ...... 39 1.3.5 FLT3 TKIs and role post stem transplantation ...... 40 1.3.6 Molecular mechanisms of resistance to TKIs ...... 40 1.3.7 Signalling pathways related to FLT3 ...... 43 1.4 MASS SPECTROMETRY ...... 50 1.5 HYPOTHESIS ...... 58 1.6 AIMS ...... 58 2 MATERIALS AND METHODS ...... 59

2.1 MATERIALS ...... 59 2.1.1 Reagents and buffers ...... 59 2.1.2 Cell lines ...... 62 2.1.3 Drugs ...... 62 2.2 METHODS ...... 63 2.2.1 Cell culture techniques ...... 63 2.2.2 Analytical techniques ...... 65

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3 RESULTS AND ANALYSIS...... 73

3.1 SIGNALLING AND CELL BIOLOGICAL EFFECT ANALYSIS ...... 74 3.1.1 Identification of optimal components for FLT3 signalling studies ...... 74 3.1.2 Examination of response to FL ...... 80 3.1.3 Selection of TKI and cell response to FLT3 inhibition or stimulation ...... 86 3.1.4 Morphological and functional cell response to FLT3 inhibition ...... 89 3.2 PROTEOMIC ANALYSIS ...... 100 3.2.1 Introduction ...... 100 3.2.2 Proteomics analysis of biologically relevant differences in expression between MV411 and OCI-AML3 in relation to FLT3 stimulation or inhibition ...... 101 3.2.3 Proteomic analysis of the differences in the nature of the expressed by MV4-11 and OCI-AML3 cells during treatment ...... 110 3.2.4 Analysis of individual proteins linked to specific biological responses in order to identifycandidate proteins for clinical exploitation ...... 117 4 CONCLUSIONS AND DISCUSSION ...... 122

4.1 SIGNALLING AND CELL BIOLOGICAL EFFECT EXPERIMENTS ...... 123 4.2 PROTEOMIC ANALYSIS ...... 125 5 FUTURE WORK ...... 128 REFERENCES ...... 129 APPENDIX 1 - OVERVIEW OF CURRENTLY AVAILABLE ACUTE MYELOID LEUKAEMIA (AML) HUMAN CELL LINES AND THEIR CHARACTERISTICS...... 146 APPENDIX 2 - LIST OF THE TOTALITY OF PROTEINS IDENTIFIED FROM THE GENERATED PROTEOMIC DATA, UTILISING THE STRING TOOL...... 147 APPENDIX 3 - CHANGES IN PROTEIN EXPRESSION IN OCI-AML3 AND MV4-11 CELL LINES. SWATH-MS ANALYSIS RAW DATASETS ...... 152 APPENDIX 4 - LIST OF PROTEIN IDENTITIES FROM PATHWAY DOWNREGULATED BY THE COMBINATION OF QUIZARTINIB AND FL IN MV4-11 CELL LINE ...... 153 APPENDIX 5 - LIST OF PROTEIN IDENTITIES FROM THE CELL CYCLE PATHWAY UPREGULATED BY THE COMBINATION OF QUIZARTINIB AND FL IN MV4-11 CELL LINE ...... 156

Total word count: 32259

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LIST OF FIGURES

Figure 1. The molecular and cytogenetic landscape in AML...... 17 Figure 2. Schematic representation of the FLT3 receptor with bound FLT3 (FL)...... 24 Figure 3. Protein and signal cascade downstream from activated FLT3...... 27 Figure 4. Schematic summary of the FLT3 signalling pathway and altered regulation ...... 28 Figure 5. Representation of the juxtamembrane domain configuration of FLT3...... 30 Figure 6. Representation of a FLT3 molecule and the potential mechanism of inhibition through TKI...... 37 Figure 7. Schematic representation of the different types and mechanisms of resistance to FLT3 inhibitors...... 41 Figure 8. Detailed representation of the potential mechanisms of resistance to FLT3 inhibitors ..... 43 Figure 9. JAK/STAT signalling pathway showing a step-wise process activation...... 45 Figure 10. Diagram of the interactions of the MAPK pathway...... 47 Figure 11. Diagram of the PI3K/AKT pathway...... 49 Figure 12. Schematic representation of the components of a mass spectrometer...... 51 Figure 13. Schematic representation of the stages of tandem mass spectrometry...... 54 Figure 14. SWATH MS- Data Independent Acquisition method ...... 56 Figure 15. Schematic representation of the difference between MRM and SWATH analysis...... 57 Figure 16. Initial flow cytometry dot plots illustrating the gating technique employed for survival testing in MV4-11 cell ...... 76 Figure 17. Flow cytometry dot plot and contour plot illustrating gating techniques of the MV4-11 subpopulations (alive and dead cells) ...... 77 Figure 18. Histograms illustrating cell viability in MV4-11 through differing permeability to propidium iodide (PI) ...... 77 Figure 19. Histogram demonstrating surface expression of annexin V by OCI-AML3 cells confirming apoptotic cells are located with the dead cell population ...... 78 Figure 20. Representation of protein concentration curve based on protein assay and comparison with BSA curve...... 79 Figure 21.Representations of down-regulation of expression levels of CD135 (receptor for FL) in MV4-11 and OCI-AML3 cells before and after exposure to FL...... 81 Figure 22. OCI AML3 cell line response to stimulation with FL ...... 82 Figure 23. MV4-11 cell line post FL stimulation ...... 83 Figure 24. The morphological features of OCI AML3 (left panel) and possible response to FL (right panel)...... 84 Figure 25. The morphological features of MV4-11 (left panel) and following exposure to FL (right panel)...... 84 Figure 26. Inhibitory response demonstrated in MV4-11 cells following treatment with Quizartinib at different doses...... 86 Figure 27. Inhibitory response demonstrated in MV4-11 cells following treatment with at different doses...... 87 Figure 28. Inhibitory response demonstrated in MV4-11 cells following treatment with at different doses...... 87 Figure 29. CD135 expression and response to Quizartinib in MV4-11 ( blue) and OCI-AML3 cells (red) ...... 88 Figure 30. High power image showing morphological changes in MV4-11cells at 2hr post Quizartinib treatment ...... 90 Figure 31. The time course of morphological changes observed in OCI-AML3 and MV4-11 cells following exposure to Quizartinib ...... 91

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Figure 32. Flow cytometry contour plot of MV4-11 cells illustrating the separation of the events identified: live cells (blue) and dead cells (green)...... 92 Figure 33. Flow cytometry analysis of FSC in MV4-11 cells following treatment with Quizartinib ...... 93 Figure 34. Flow cytometry analysis of SSC in MV4-11 cells following treatment with Quizartinib ...... 93 Figure 35. CFSE stained OCI-AML3 cells at 24 and 72 hours...... 95 Figure 36. CFSE stained MV4-11 cells at 24 and 72 hours...... 96 Figure 37. Flow cytometry analysis of survival in MV4-11 cells following treatment with Quizartinib...... 97 Figure 38. Flow cytometry analysis of survival in MV4-11 and OCI AML3 cells at 24 hrs...... 98 Figure 39. Flow cytometry analysis of survival in MV4-11 and OCI AML3 cells at 48 hrs...... 98 Figure 40. Change in the number of proteins affected by Quizartinib for OCI-AML3 and MV4-11 cell lines...... 104 Figure 41. Level of quantitative change affecting proteins during treatment with Quizartinib for OCI-AML3 and MV4-11 cell lines...... 104 Figure 42. Change in the number of proteins affected by FL for OCI-AML3 and MV4-11 cell lines...... 107 Figure 43. Level of quantitative change affecting proteins during treatment with FL for OCI-AML3 and MV4-11 cell lines...... 107 Figure 44. Level of quantitative change affecting proteins during treatment with FL for OCI-AML3 and MV4-11 cell lines...... 108 Figure 45. Level of quantitative change affecting proteins during treatment with both FL and Quizartinib for OCI-AML3 and MV4-11 cell lines...... 109 Figure 46. Representation of the processes affected by the downregulated molecules following exposure to Quizartinib...... 112 Figure 47. Representation of the processes affected by molecules upregulated by exposure to Quizartinib...... 113 Figure 48. Representation of downregulated cellular functions changed by exposure to FL...... 114 Figure 49. Representation of downregulated cellular functions changed by exposure to Quizartinib in the presence of FL...... 114 Figure 50. Representation of downregulated cellular functions changed by exposure to Quizartinib in the presence of FL...... 115 Figure 51. Representation of upregulated cellular functions changed by exposure to Quizartinib in the presence of FL...... 116 Figure 52. Analysis of the functional grouping of proteins functioning in the proliferation pathway (upregulated proteins)...... 118 Figure 53. Analysis of the functional grouping of proteins functioning in the apoptosis pathway (downregulated proteins)...... 119 Figure 54. Analysis of the functional grouping of proteins functioning in the proliferation pathway (upregulated proteins)...... 120

N.B. All figures are new unless otherwise stated.

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LIST OF TABLES

Table 1. Classification of the class I, II and III mutations and their significance and role in AML. 13 Table 2. The French-American-British classification for AML (1976)...... 14 Table 3. WHO classification of AML and related neoplasms (2016)...... 15 Table 4. Prognostic-risk groups in AML based on cytogenetic and molecular profile ...... 16 Table 5. Proposed classification of transplant procedures for adult AML (2015) ...... 19 Table 6. Response criteria for AML ...... 21 Table 7. Novel therapies in clinical development in AML ...... 22 Table 8. Summary of available FLT3 inhibitors and overview of their activity spectra...... 35 Table 9. Clinical trial results of TKIs in mono- or combination therapy in AML...... 36 Table 10. BSA dilutions for protein concentration assay. BSA curve determination ...... 64 Table 11. Illustration of a 12-well plate and schematic representation of a protein assay ...... 65 Table 12. Overview of the significant protein expression changes in the OCI-AML3 and MV4-11 cell lines...... 103 Table 13. Isolated proteins expressed during cellular apoptosis in MV4-11 cell line ...... 105

N.B. All tables are new unless otherwise stated.

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ABBREVIATIONS

AATYK Apoptosis Associated AML Acute Myeloid Leukaemia ATP Adenosine Triphosphate BCL2 B-cell lymphoma 2 BTG-2 B-cell translocation gene 2 CCND3 D3 CDKN1B Cyclin-dependent kinase inhibitor 1B CEBPα CCAAT/Enhancer Binding Protein Alpha c-KIT mast/stem cell receptor CR Complete Remission DUSP6 Dual Specificity 6 Evi-2 Ectropic Viral Integration Site 2 FL FLT3 ligand FLT3 FMS-like 3 FMS colony stimulating factor 1 receptor Frat1 Frequently Rearranged In Advanced T-Cell Lymphomas 1 GADD45 Growth Arrest And DNA Damage Inducible Alpha Galpha15 Guanine nucleotide-binding protein subunit alpha GP49B Ig superfamily-related, type I transmembrane IL2Rα The 2 (IL2) receptor alpha ITD Internal Tandem Duplication JM Juxtamembrane JM-B Juxtamembrane Binding JM-S Juxtamembrane Switch Motif JM-Z Juxtamembrane Zipper LM Length Mutation maf-B MAF BZIP B MAID Maternal-Id like MCL1 Myeloid Leukaemia Cell differentiation protein MDS Myelodysplastic Syndrome MRD Minimal Residual Disease MYC V-Myc Avian Myelocytomatosis Viral Homolog NPM1 Nucleophosmin 1

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OS Overall Survival p16ink4A cyclin-dependent kinase inhibitor 2A PAK1 P21 (RAC1) Activated Kinase 1 PCR Polymerase Chain Reaction PDGFRα/β Platelet-Derived alpha and beta PGE-R Prostaglandin E synthase PIA Plasma Inhibitory Activity Pim 1, 2 Proto-oncogene with serine/threonine PR Partial Remission RAR γ Retinoic Acid Receptor Gamma RB2/p130 RB Transcriptional Corepressor Like 2 RGS2 Regulator of signalling RR Relapse Risk RTK SDS-PAGE Sodium Dodecyl Sulphate - Polyacrylamide Gel Electrophoresis SOCS 2, 3 Suppressor of signalling TKD Tyrosine Kinase Domain TKIs Tyrosine Kinase Inhibitors TNF Tumour necrosis factor TTPA Alpha Tocopherol Transfer Protein WDR87 WD Repeat Domain 87 Xbp1 X-Box Binding Protein 1

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DECLARATION

No portion of the work referred to in this thesis has been submitted in support of an application for another degree or qualification of this or any other university or other institute of learning.

COPYRIGHT STATEMENT

i. The author of this thesis (including any appendices and/or schedules to this thesis) owns certain copyright or related rights in it (the “Copyright”) and s/he has given The University of Manchester certain rights to use such Copyright, including for administrative purposes. ii. Copies of this thesis, either in full or in extracts and whether in hard or electronic copy, may be made only in accordance with the Copyright, Designs and Patent Act 1988 (as amended) and regulations issued under it or, where appropriate, in accordance with licensing agreements which the University has from time to time. This page must form part of any such copies made. iii. The ownership of certain Copyright, patents, designs, trademarks and other intellectual property (the “Intellectual Property”) and any reproductions of copyright works in the thesis, for example graphs and tables (“Reproductions”), which may be described in this thesis, may not be owned by the author and may be owned by third parties. Such Intellectual Property and Reproductions cannot and must not be made available for use without the prior written permission of the owner(s) of the relevant Intellectual Property and/or Reproductions. iv. Further information on the conditions under which disclosure, publication and commercialisation of this thesis, the Copyright and any Intellectual Property and/or Reproductions described in it may take place is available in the University IP Policy (see http://documents.manchester.ac.uk/DocuInfo.aspx?DocID=24420) in any relevant thesis restriction declarations deposited in the University Library, The University Library’s regulations (see http://www.library.manchester.ac.uk/about/regulations/) and in The University’s policy on Presentation of Theses.

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ACKNOWLEDGEMENT

Firstly, I would like to thank my supervisor, Dr John Burthem for all the advice and guidance and for the opportunity to pursue a MD in his laboratory. A big thanks to all my colleagues in the St Mary’s Laboratory, particularly Dr Karen Rees-Unwin and Dr Julie Adams for their continued support throughout my MD. A thank you also goes to Dr Ciaren Graham and Dr Richard Graham for providing the mass spectrometry analysis and expertise. A big thanks to the Horace Hayhurst Foundation for providing funding for this project and Dr Eleni Tholouli and Dr Fiona Dignan at Manchester Royal Infirmary for this incredible opportunity. Finally, a special thanks to my husband Allan for his infinite support and patience these last few years!

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ABSTRACT

FMS-like tyrosine kinase 3 (FLT3) is a class III receptor tyrosine kinase. Mutations affecting the FLT3 gene are frequent in acute myeloid leukaemia (AML) and are detected in up to 35% of patients, where they are associated with shorter remission rates and higher relapse risk. FLT3 is therefore an important potential target for therapy of AML. However, to date, inhibitors of FLT3 tyrosine kinase have had limited clinical success. This thesis employs cell line models of AML assessed by proteomic analysis, aiming to address whether proteins associated with FLT3-response can be identified and could form part of novel strategies to improve outcome.

Two cell lines: MV4-11 (FLT3/ITD) and OCI-AML3 (wtFLT3) were assessed for their suitability as models to test FLT3 ligand (FL) or FLT3-inhibitor effect. Each was shown to express functional FLT3 receptor and to upregulate pERK signalling in response to FL, which was inhibited in each case by FLT3 inhibitor drugs. However, the FLT3/ITD cell line MV4-11, but not OCI-AML3, also demonstrated high baseline signal activation of pERK and in cell biological testing Quizartinib induced apoptosis and abolished proliferation only in FLT3/ITD MV4-11 cells. The FLT3 inhibitor Quizartinib was selected for detailed study, based on literature evaluation and on dose-dependent inhibition of pERK in each cell line.

A proteomic approach (Sequential Window Acquisition of all theoretical fragment-ion spectra mass spectrometry (SWATH-MS)) was then used to identify whether protein expression differed between the sensitive (MV4-11) and resistant cell (OCI-AML3) lines at baseline or in conditions of stimulation or inhibition. These analyses showed that MV4- 11 and OCI-AML3 lines differed in their response to Quizartinib, but that the most marked changes required the additional presence of FL. Bioinformatic analysis of responses in the different conditions demonstrated that FLT3 pathways predominantly involved the processes of cell growth, apoptosis or replication (consistent with the findings in section 3.1). The changes affecting those processes were much more marked in MV4-11 cells, and the bioinformatic study of the proteins identified candidate molecules for therapeutic targeting such as BCL2 and ROCK1 pathway.

Although these findings should be regarded as preliminary and requiring confirmation in larger test sets, this thesis shows the potential value of this approach to identify additional target proteins for therapy in patients with FLT3/ITD mutated AML.

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1 INTRODUCTION

1.1 Acute myeloid leukaemia (AML)

1.1.1 Introduction

Acute myeloid leukaemia (AML) is a clonal disorder of the haematopoietic stem cell, characterised by maturation arrest and clonal expansion of immature cells (blasts). AML is a very heterogeneous disease in terms of behaviour, response to treatment and outcome. The incidence of AML is 2.5-3 cases for every 100,000 people per year with a median age at presentation of 65 years of age.1 Cure rates have improved since the 1970s when overall survival was 15% at 5 years to around 40% for patients under 65 years old,2,3 prognosis in the elderly population remains poor.2 At present, 70% of patients aged 65 or older will die of AML with currently available treatments within 1 year of diagnosis.3

1.1.2 Pathogenesis

AML arises most frequently as a de novo disease, but it can also occur in patients with prior haematological disorders or may be secondary to previous treatment (therapy-related AML), particularly following exposure to alkylating agents or radiation.4 Chromosomal rearrangements and molecular changes underlie the pathogenesis of AML. In 97% of AML cases, genetic mutations are identified without a large chromosomal rearrangement.5 Therefore, a “two-hit” model of leukaemogenesis has been developed as a base that explains and classifies the different mutations associated with AML. This model hypothesizes that a class I mutation induces the activation of the pro-proliferative pathways together with a class II mutation which impairs the normal differentiation of haematopoietic precursors to generate leukaemia. 6 The two-hit model suggests that the pathogenesis and hence the behaviour of AML relies on the interaction of different types of mutations. Nevertheless, many different types of mutation are now recognised to contribute to AML (Table 1), and the exact mechanism of leukaemogenesis and the contribution of the individual mutations to the generation of AML remains to be determined in many cases.

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Table 1. Classification of the class I, II and III mutations and their significance and role in AML.

Classification Significance Mutations

Class I Provide Cellular proliferative • FLT3 • NRAS (Constitutive signal and / or survival advantage • KIT • KRAS Transduction) • JAK1 • PTPN11 • JAK3 • CBL

Class II Impaired cellular • PML-RARα • GATA2 (Deregulated gene differentiation • NPM1 • RUNZ1- expression) • CBFβ-MYH11 RUNX1T1 • CEBPα • MLL fusion • RUNX1 • DEK-NUP214

Class III Epigenetic / chromatin • MLL-PTD • BCORL1 (Epigenetic Mutations) changes • TET2 • STAg2 • DNMT3A • SMC3 • IDH1/2 • SMC1A • EZH2 • RAD21 • ASXL1 • TP53 • BCOR • WT1

Legend: Mutations in AML may be divided in 3 classes: I, II and III. Class I mutations affect constitutive , Class II mutations affect and Class III encompasses epigenetic mutations.

Abbreviations: FLT3= FMS-like tyrosine kinase 3; KIT= proto-oncogene receptor tyrosine kinase; CBL= Casitas B-lineage lymphoma; JAK1 and 3= 1 and 3; NRAS= Neuroblastoma Ras viral oncogene; KRAS= viral proto-oncogene; PTPN11= Protein Tyrosine Phosphatase Non-Receptor Type 11; PML-RARα= Promyelocytic leukaemia-retinoic acid receptor alpha; NPM1=Nucleophosmin 1; CBFβ- MYH11= Core-binding factor subunit beta-Myosin heavy chain 11; CEBPα= CCAAT Enhancer Binding Protein Alpha; RUNX1= Runt related transcription factor 1; GATA2= GATA binding protein 2; RUNX1- RUNX1T1= RUNX1 translocation partner 1; MLL= myeloid/lymphoid leukaemia or mixed lineage leukaemia; DEK-NUP214= DEK proto-oncogene-Nucleoporin 214; MLL-PTD= MLL partial tandem duplication; TET2= Tet Methylcytosine Dioxygenase 2; DNMT3A= DNA Methyltransferase 3 Alpha; IDH1/2= Isocitrate dehydrogenase 1/2; EZH2= Enhancer Of Zeste 2 Polycomb Repressive Complex 2 Subunit; ASXL1= AXL receptor tyrosine kinase 1; BCOR= BCL6 corepressor; BCORL1= BCL6 corepressor like 1; STAG2= stromal 2; SMC3= Structural Maintenance Of 3; SMC1A= Structural Maintenance Of Chromosomes 1A ; RAD21= RAD21 Cohesin Complex Component ; TP53= Tumour protein ; WT1= Wilms Tumour 1.

1.1.3 Clinical presentation and diagnosis

The clinical manifestations of AML relate to the clonal expansion of myeloid blasts in the bone marrow, peripheral blood and, rarely, in other organs. At presentation, a picture of leukocytosis and bone marrow failure (anaemia and thrombocytopenia) is common. Constitutional symptoms (such as fatigue, weight loss, fever and night sweats) are also frequent, but lymphadenopathy and organomegalies are infrequent findings.

The diagnosis of AML is made by demonstrating a blast count > 20% in the bone marrow or peripheral blood, followed by the determination of a myeloid origin of the blasts through morphological findings such as Auer rods (azurophilic, needle-shaped cytoplasmic

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7 inclusion bodies), myeloperoxidase positivity or typical immunophenotype. AML can also be diagnosed in extramedullary tissue infiltrates or by documenting a t(8;21), inv(16) or t(15;17) mutation independent of the blast counts.8 If treatment is not commenced promptly, the prognosis is very poor with death occurring within months of the diagnosis due to infectious or bleeding complications.

1.1.4 Classification

The first system used to classify the different subtypes of AML was the French–American– British classification system, established in 1976.9 (Table 2) This defines the AML subtypes based on morphological and cytochemical characteristics of the blasts and identified eight subtypes (M0 to M7).

Table 2. The French-American-British classification for AML (1976).

Type Name M0 acute myeloblastic leukaemia, minimally differentiated M1 acute myeloblastic leukaemia, without maturation M2 acute myeloblastic leukaemia, with granulocytic maturation M3 promyelocytic, or acute promyelocytic leukaemia (APL) M4 acute myelomonocytic leukaemia M4eo myelomonocytic together with bone marrow eosinophilia M5 acute monoblastic leukaemia (M5a) or acute monocytic leukaemia (M5b) M6 acute erythroid leukaemias, including erythroleukemia (M6a) and very rare pure erythroid leukaemia (M6b) M7 acute megakaryoblastic leukaemia Table adapted from the FAB classification (1976) 9

Legend: Classification of AML, based on morphology, as described by the French-American-British classification of 1976.

In 2001, due to the necessity to incorporate the diagnostic advances in the cytogenetics and molecular fields, the World Health Organisation (WHO) introduced a new classification system. This initial classification has had further revised versions in 2008 and 2016.10’11 As a consequence of integrating the diagnostic advances to incorporate genetics, morphology and immunophenotype, AML can be classified into 6 major entities: (1) AML with recurrent genetic abnormalities, (2) AML with myelodysplasia-related features, (3) therapy-related AML, (4) AML not otherwise specified, (5) myeloid sarcoma (6) myeloid proliferation related to Down syndrome and the corresponding subtypes (Table 3).11

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Table 3. WHO classification of AML and related neoplasms (2016). AML type Genetic abnormalities AML with recurrent genetic abnormalities AML with t(8:21)(q22;q22); RUNX1-RUNX1T1 AML with inv(16)(p13.1q22) or t(16;16)(p13.1;q22); CBFB-MYH11 APL with PML-RARA AML with t(9;11)(p21.3;q23.3); MLLT3-KMT2A ML with t(6;9)(p23;q34.1); DEK-NUP214 AML with inv(3)(q21.3q26.2) or t(3;3)(q21.3;q26.2); GATA2, MECOM AML (megakaryoblastic) with t(1;22)(p13.3;q13.3); RBM15-MKL1 AML with BCR-ABL1 (provisional entity) AML with mutated NPM1 AML with biallelic mutations of CEBPA AML with mutated RUNX1 (provisional entity) AML with myelodysplasia-related changes

Therapy-related myeloid neoplasms

AML, Not Otherwise Specified (NOS) AML with minimal differentiation AML without maturation AML with maturation Acute myelomonocytic leukaemia Acute monoblastic/monocytic leukaemia Acute erythroid leukaemia Pure erythroid leukaemia Acute megakaryoblastic leukaemia Acute basophilic leukaemia Acute panmyelosis with myelofibrosis Myeloid sarcoma Myeloid proliferations related to Down Transient abnormal myelopoiesis syndrome ML associated with Down syndrome Table adapted from WHO 201611

Legend: Classification of and related neoplasms, as described by the World Health Organisation classification in 2016.

Abbreviations: AML=acute myeloid leukaemia; APL=acute promyelocytic leukaemia; ML= myeloid leukaemia; WHO=World Health Organization

1.1.5 Prognostic factors and groups

The assessment of the prognostic factors plays an essential role at diagnosis and will aid in the classification of patients into risk categories. This will then influence the decision on the management strategy to be undertaken in each individual case.

Age and performance status (ECOG or comorbidities) can predict the treatment-related mortality (TRM) of each patient and will help guide the decision on the intensity of the treatment. Patients with advanced age or poor performance status, as defined by the Eastern cooperative oncology group (ECOG) performance score are associated with lower rates of complete remission and reduced overall survival. 2’12 Nevertheless, the most important 15 factors to bear in mind in risk stratification are the cytogenetic abnormalities that will impact on CR and OS in AML. Therefore, AML can be stratified into favourable, intermediate and adverse prognostic risk groups based on the cytogenetic profile of the disease (Table 4).

Table 4. Prognostic-risk groups in AML based on cytogenetic and molecular profile Prognostic-risk Cytogenetic profile Cytogenetic profile and molecular group abnormalities Favourable t(8:21)(q22;q22) t(8:21)(q22;q22) with no c-KIT mutation inv(16)(p13;1q22) inv(16)(p13;1q22) t(15;17)(q22;q12) t(15;17)(q22;q12) Mutated NPM1 without FLT3/ITD (CN- AML) Mutated biallelic CEBPA (CN-AML) Intermediate CN-AML t(9;11)(p22;q23) t(8:21)(q22;q22) with mutated c-KIT Cytogenetic abnormalities not CN-AML other than those included in the included in the favourable or adverse favourable or adverse prognostic group prognostic risk groups t(9;11)(p22;q23) Cytogenetic abnormalities not included in the favourable or adverse prognostic risk groups Adverse inv(3)(q21q26.2) TP53 mutation, regardless of cytogenetic t(6;9)(p23;q34) profile 11q abnormalities other than t(9;11) CN with FLT3/ITD − 5 or del(5q) CN with DNMT3A − 7 CN with KMT2A-PTD Complex karyotype inv(3)(q21q26.2) t(6;9)(p23;q34) 11q abnormalities other than t(9;11) − 5 or del(5q) − 7 Complex karyotype Legend: Based on the cytogenetic profile of the disease, AML can be stratified into favourable, intermediate and adverse prognostic risk groups.

Abbreviations: AML=acute myeloid leukaemia; ITD=internal tandem duplication

The chromosomal rearrangements t(8;21), t(15;17) or inv(16) all confer a favourable prognosis8’13 with a 3-year OS of 66% in patients under 69 years and 33% those aged greater than 60 years of age.14 In contrast, a complex karyotype (i.e. three or more chromosomal abnormalities in the absence of any of the recurrent genetic abnormalities identified in the WHO 2008 classification), monosomy 5 or 7, t(6;9), inv(3) or 11q changes other than t(9;11) are associated with a significantly higher risk of treatment failure and adverse prognosis.14 The intermediate prognostic risk group is mostly formed by AML with normal cytogenetics (CN-AML). 8’14

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Figure 1. The molecular and cytogenetic landscape in AML.

Image adapted from Döhner H et al. Blood 201715

Legend: Representation of the landscape in Acute myeloid leukaemia with the addition of molecular and cytogenetic testing. Figure reveals the complexity and intricacy of defining AML prognostic groups.

Gene mutations have helped further refine the existing risk stratifications that are based on cytogenetic changes alone. Among patients with t(8;21), the presence of a c-KIT mutation significantly increases the risk of relapse, and decreases OS to levels comparable to those of patient with intermediate-risk AML.16’17’18 Although there is some evidence that the presence of c-KIT mutations similarly lowers prognosis in patients with inv(16), 19 recent studies have failed to show any prognostic impact in this subset of cases.16’20

Molecular changes play a crucial role in refining the prognosis of patients with CN-AML,15 (Figure 1) which includes nearly half of de novo AML cases. For example, CN-AML with mutated CEBPA or NPM1 in the absence of FLT3/ITD has a similar prognostic risk as that of AML with favourable cytogenetics.8’21 It is nevertheless believed that the favourable prognostic impact of the CEBPA mutations only applies to the bi-allelic mutation.22 In contrast, several studies 21’18 of event-free survival (EFS) and OS in patients with CN-AML of 60 years of age have consistently demonstrated the adverse prognosis of the presence of FLT3/ITD. 23’24

Therefore, CN-AML with FLT3/ITD has been classified into the adverse prognostic-risk group.13’25 Several studies have shown a considerable worse prognosis in patients with higher mutant to wild-type allelic ratio26’27 similar to CEBPA mutations.

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In addition to the genetic profile at diagnosis, the response to treatment plays an important role in refining patient prognosis: patients who achieve a complete remission (CR) after induction therapy have a significantly increased survival compared with patients with resistant disease.28’29 Amongst the patients who achieve a CR, other factors can influence survival such as the rate of correction of cytopenias, with a shorter survival observed in those with prolonged thrombocytopenia.29 It has become essential to monitor minimal residual disease (MRD) in patients who achieve a CR using real-time PCR or flow cytometry techniques. It is now clear that persistently elevated levels of RUNX1-RUNX1T1 transcripts after induction chemotherapy in patients with t(8;21) AML (despite its favourable risk classification), are associated with an increased incidence of relapse.30’31 Similarly, detecting MRD by flow cytometry in patients with intermediate-risk disease, represents an independent predictor of relapse32’33 and will impact on management decisions.34

1.1.6 Treatment

1.1.6.1 Conventional therapy

Patients with AML require chemotherapy in order to achieve a complete remission. Therefore, eligible patients should receive intensive chemotherapy as induction therapy, followed by consolidation therapy to consolidate the response and ensure a lasting remission.

The gold-standard of induction therapy uses a combination of antracyclines + cytarabine: daunorubicin (60mg/m2) / idarubicin (12mg/m2) and cytarabine (100-200mg/m2), better known as the “7+3” regimen, which combines 7 days of continuous infusion cytarabine with 3 days of anthracycline. With this regime, the CR rates are 60-80% for younger adults and 40-60% for patients >60 years of age.8’35’36

Response to chemotherapy should be evaluated at 14 days after induction therapy with a bone marrow aspirate and trephine biopsy.8 For patients who show complete remission at this stage, the options vary depending on prognostic risk groups. In the favourable prognostic group, the consolidation chemotherapy consists of 2-4 cycles of intermediate- dose Cytarabine (IDAC) (1000-1500 mg/m2 IV over 3h every 12h) for young patients (18- 60/65 years old). For young patients with intermediate-risk disease, the options include allogeneic HSCT from matched-related or unrelated donor or 2-4 cycles of IDAC (1000- 1500 mg/m2 IV over 3h every12h) or high-dose therapy and autologous HSCT.

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For young patients with high-risk disease, consolidation should be with allo-HSCT from matched-related or unrelated donor. Allo-HSCT significantly prolongs EFS and OS in some patients with intermediate-risk and in most with adverse-risk AML and should therefore be offered as first-line consolidation in eligible patients.37’38’39’40 (Table 5).

The evidence grading used for these recommendations was not based on a formal evidence review, but rather on a broad classification taking into account I) evidence from one or more randomised trials; II) evidence from one or more well-designed clinical trial without randomisation, cohort or case-control studies and III) evidence based on descriptive studies, expert committees or expert opinions based on clinical experience.41

Table 5. Proposed classification of transplant procedures for adult AML (2015) Disease response Sibling donor Unrelated Alternative Autologous allogeneic donor donor SCT SCT allogeneic SCT allogeneic SCT CR1 (low risk CO / II D / II GNR / II CO / I

CR1 (intermediate risk) S / II CO / II D / II S / I

CR1 (high risk) S / II S / II CO / II CO / I

CR2 S / II S / II CO / II CO / II

CR3 incipient relapse S / III CO / III D / III GNR / III

Relapse/refractory CO / II CO / II D / II GNR / III

Legend: The evidence grading used for these recommendations: I) evidence from one or more randomised trials; II) evidence from one or more well-designed clinical trial without randomisation, cohort or case-control studies and III) evidence based on descriptive studies, expert committees or expert opinions based on clinical experience.

Abbreviations: allo-HSCT=allogeneic haematopoietic stem cell transplant; CR1,2,3=first, second, third complete remission; S=standard of care; CO=clinical opinion; D=developmental; GNR=generally not recommended.

Almost 25-50% of patients show persistent disease at initial assessment following induction chemotherapy42 and therefore require re-induction therapy (Table 6). The optimal choice of re-induction regimens has not been established and expected CR rates are around 50%.13’43’44

For patients with refractory or relapsed disease options for salvage chemotherapy include FLAG-Ida (Fludarabine 30 mg/m2 IV, day2-6; cytarabine 1500-2000 mg/m2 IV, day2-6; idarubicin 10 mg/m2 IV, day2-4; G-CSF 5 mg/kg, SC), MEC (Mitoxantrone 8 mg/m2, day1-5; etoposide 100 mg/m2, day1-5; cytarabine 1000 mg/m2, day1-5) or allogeneic HSCT.

19

To date, an optimal management approach for elderly patients (>60/65 years of age) has not been established. These patients are more likely to have high-risk AML at presentation and more comorbidities with higher ECOG score, making treatment decisions very difficult. The treatment-related mortality (TRM) should be weighed against potential benefit. However, induction therapy improves survival in patients over the age of 65 when compared with supportive care and palliative chemotherapy, and should be attempted whenever possible.45

Eligible patients (ie. low ECOG score) should receive conventional induction therapy to increase their chances of achieving remission. If complete remission is achieved, consolidation in the favourable-risk group generally consists of 2-3 cycles of IDAC (500- 1000 mg/m2 IV over 3h every 12h) for patients 60 years of age or older. For elderly patients with intermediate- or high-risk disease, consider allogeneic HSCT (in patients with low HCT-CI) or investigational therapy.15

On the other hand, the management of patients non-eligible for induction chemotherapy remains a challenge. Hypomethylating agents (azacitidine and decitabine) traditionally used in the treatment of myelodysplastic syndrome (MDS), have shown efficacy in elderly patients with AML.46 A 2012 randomized trial in patients 65 years or older comparing decitabine with supportive care or low dose cytarabine showed a significant improvement in OS with decitabine in this patient group.47

In a recent trial comparing azacitidine with supportive care, low-dose cytarabine or standard induction therapy in elderly patients (65 years or older), there was no significant median OS improvement observed, however it suggested a benefit in patients with high- risk disease or previous MDS.48 Therefore, elderly patients with adverse cytogenetics may benefit from treatment with azacitidine 75 mg/m2, SC, d1-7, every 4 weeks, until progression or decitabine 20 mg/m2, IV, d1-5, every 4 weeks, until progression. Responders do so in the first few weeks of commencing treatment, making it unlikely to achieve a response beyond 3 cycles if they haven’t done so already.

Other options for this patient group would be low dose cytarabine (20 mg every 12h, SC, day 1-10, every 4 weeks until progression) but this is not recommended in patients with adverse-risk genetics. Alternative options, for very frail patients unable to tolerate hypomethylating agents or cytarabine or patients who do not wish to have treatment, would be best supportive care and potentially Hydroxyurea to manage blast counts.

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Table 6. Response criteria for AML

Response type Definition CR without minimal residual If studied pre-treatment, CR with negativity for a genetic marker by RT-qPCR,

disease (CRMRD-) or CR with negativity by MFC Complete remission (CR) Bone marrow blasts <5%; absence of circulating blasts and blasts with Auer 9 rods; absence of extramedullary disease; ANC ≥1.0 x 10 /L (1000/µL); platelet 9 count ≥100 x 10 /L (100 000/µL) 9 CR with incomplete All CR criteria except for residual neutropenia (<1.0 x 10 /L [1000/µL]; platelet haematologic recovery (CRi) 9 count <100 x 10 /L [100 000/µL]) Morphologic leukaemia-free Bone marrow blasts <5%; absence of blasts with Auer rods; absence of state (MLFS) extramedullary disease; no haematologic recovery required Partial remission (PR) All haematologic criteria of CR; decrease of bone marrow blast percentage to 5% to 25%; and decrease of pre-treatment bone marrow blast percentage by at least 50% Primary refractory disease No CR or CRi after 2 courses of intensive induction treatment; excluding patients with death in aplasia or death due to indeterminate cause Death in aplasia Deaths occurring ≥7 d following completion of initial treatment while cytopenic; with an aplastic or hypoplastic bone marrow obtained within 7 d of death, without evidence of persistent leukaemia Death from indeterminate Deaths occurring before completion of therapy, or <7 d following its completion; cause or deaths occurring ≥7 d following completion of initial therapy with no blasts in the blood, but no bone marrow examination available Haematologic relapse (after Bone marrow blasts ≥5%; or reappearance of blasts in the blood; or development

CRMRD-, CR, CRi) of extramedullary disease Molecular relapse (after If studied pre-treatment, reoccurrence of MRD as assessed by RT-qPCR or by

CRMRD-) MFC

Stable disease Absence of CRMRD-, CR, CRi, PR, MLFS; and criteria for PD not met Progressive disease (PD) Evidence for an increase in bone marrow blast percentage and/or increase of absolute blast counts in the blood: • >50% increase in marrow blasts over baseline (a minimum 15% increase is required in cases with <30% blasts at baseline; or persistent marrow blast percentage of >70% over at least 3 mo; without at least a 100% 9 improvement in ANC to an absolute level (>0.5 x 10 /L [500/µL], and/or 9 platelet count to >50 x 10 /L [50 000/µL] non-transfused); or 9 • >50% increase in peripheral blasts (WBC x % blasts) to >25 x 10 /L (>25 000/µL) (in the absence of differentiation syndrome); or • New extramedullary disease Adapted from Döhner H et al. Blood 201715

Legend: Detailed description of the response assessments used in Acute myeloid leukaemia.

Abbreviations: RT-qPCR=reverse transcription quantitative polymerase chain reaction; MFC=multi- parameter flow cytometry; ANC=absolute neutrophil count; IDH=isocitrate dehydrogenase; MLFS=morphologic leukaemia-free state; WBC=white blood cell.

1.1.6.2 Novel agents

AML is an important field for new drug investigation.19’20 Novel therapies are usually first evaluated in patients with relapsed/refractory disease or in older patients not considered candidates for standard intensive chemotherapy. Novel therapies in preclinical or clinical development may be categorized as inhibitors, epigenetic modulators, new cytotoxic agents, mitochondrial inhibitors including apoptosis therapies, therapies targeting specific oncogenic proteins, therapeutic and immune checkpoint antibodies and cellular immunotherapies, and therapies targeting the AML microenvironment (Table 7).

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Table 7. Novel therapies in clinical development in AML Type Examples Protein kinase inhibitors • FLT3 inhibitors (, Quizartinib, , ) • KIT inhibitors • PI3K/AKT/mTOR inhibitors • Aurora and polo-like kinase inhibitors, CDK4/6 inhibitors, CHK1, WEE1, and MPS1 inhibitors • SRC and HCK inhibitors Epigenetic modulators • New DNA methyltransferase inhibitors (SGI-110) • HDAC inhibitors • IDH1 and IDH2 inhibitors • DOT1L inhibitors • BET-bromodomain inhibitors Chemotherapeutic agents • CPX-351 • Vosaroxin • Nucleoside analogs Mitochondrial inhibitors • Bcl-2, Bcl-xL, and Mcl-1 inhibitors • Caseinolytic protease inhibitors Therapies targeting oncogenic • Fusion transcripts targeting proteins • EVI1 targeting • NPM1 targeting • Hedgehog inhibitors Antibodies and immunotherapies • Monoclonal antibodies against CD33, CD44, CD47, CD123, CLEC12A • Immunoconjugates (eg, GO, SGN33A) • BiTEs and DARTs • CAR T cells or genetically engineered TCR T cells • Immune checkpoint inhibitors (PD-1/PD-, CTLA-4) • Anti-KIR antibody • Vaccines (eg, WT1) Therapies targeting AML • CXCR4 and CXCL12 antagonists environment • Antiangiogenic therapies

Adapted from Döhner H et al. Blood 201715

Abbreviations: BiTE=bispecific T-cell engager; CAR=chimeric antigen receptor; DART=dual-affinity retargeting molecule; HDAC=histone deacetylase; KIR=killer-cell immunoglobulin-like receptor; mTOR=mechanistic target of rapamycin; PD-1=programmed cell death protein 1; PD-L1=programmed death ligand 1; PI3K=phosphatidylinositol 3-kinase; TCR=T-cell receptor.

1.2 FLT3 mutations

1.2.1 Introduction

Acute myeloid leukaemia (AML) is a clonal disorder of the haematopoietic stem cell, characterised by maturation arrest and clonal expansion of immature cells (blasts). AML is a very heterogeneous disease in terms of behaviour, response to treatment and outcome. Cure rates have improved since the 1970s when overall survival was 15% at 5 years to around 40% for patients under 65 years old.49’50 Cytogenetic analysis is essential at diagnosis, providing information with regards to prognostic subtypes within AML. Molecular analysis provides further in-depth disease stratification, due to the identification of acquired mutations that have been proven to have prognostic significance in AML, thus explaining why not all AML patients with normal karyotype have the same prognosis, outcome or overall survival.11 22

Of the molecular lesions recognised in AML, mutations of the FMS-like tyrosine kinase 3 (FLT3) gene are the most frequently identified genetic alterations in AML, present in 30- 40% of patients.51’16 The FLT3 gene is located at 13q12 and consists of 24 exons.52 FLT3 belongs to the class III receptor tyrosine kinase (RTK) family, which also includes colony stimulating factor 1 receptor (FMS), mast/stem cell growth factor receptor (c-KIT), platelet-derived growth factor receptor alpha and beta (PDGFRα/β). Wild-type FLT3 (wt FLT3) is predominantly expressed on haematopoietic progenitor cells in the bone marrow, thymus and lymph nodes53 and this expression is lost as the haematopoietic cells differentiate. It can also be found in other tissues such as brain, placenta and gonads.54

FLT3 expression has been shown to play an important role in survival, proliferation and differentiation of cells, playing a major part in B- and T- development, but is not required for myeloid differentiation.51’55’56’57

In haematological malignancies, wt FLT3 expression is prevalent in AML (93% of AML patients), B-cell acute lymphoblastic leukaemia (up to 100% of patients), T-cell acute lymphoblastic leukaemia (87% of cases)58 and in a smaller percentage in patients with blast crisis transformation of chronic myeloid leukaemia.59’60

1.2.2 Types of Mutations

FLT3 mutations are commonly single mutations, rarely associated with other recurrent cytogenetic abnormalities, although they may be found in conjunction with nucleophosmin 1 (NPM1) mutations in approximately 38% of patients.61 AML with normal karyotype was previously considered an intermediate-risk disease, but advances in gene expression profiling have revealed a range of prognostic outcomes in this subgroup and FLT3 mutations have demonstrated a negative prognostic impact on outcome in AML in recent studies, showing a reduction in the event free survival (EFS) (9.7 months versus 19.3 months) and overall survival (OS) at 2 years (52.7% vs 72%) when compared with the wild type FLT3 (wtFLT3)group.61’62’63

The prognostic impact of FLT3 mutations depends on the type and characteristics of the mutation, as well as the ratio between mutated and non-mutated FLT3 allele load.61

Two major types of FLT3 mutation have been identified: internal tandem duplication (ITD) mutation and point mutations in the tyrosine kinase domain (TKD) (Figure 2). Deletions and deletion/insertion mutations in the juxtamembrane domain have also been reported and

23 together with the ITD mutations are sometimes referred to in the literature as length mutation (LM). These mutations have an uncertain significance to date and therefore, for the scope of this review, we shall refer to all the mutations involving the juxtamembrane domain as ITD mutations.

Early reports could not establish an association between the incidence of FLT3/ITD and age, but more recent data suggest a decrease, with an incidence of 16-20% in patients older than 60 years old as compared to up to 35% in patients 20-59 years old.64’65 Patients with FLT3/ITD mutations have a dismal prognosis with a median survival of less than a year.16

FLT3/ITD mutations are in-frame tandem duplications of 3 to 400 base pairs (bp) that map to the juxtamembrane domain. This leads to auto-dimerisation and auto-phosphorylation of the receptor in the absence of the ligand, inducing constitutive activation of the receptor tyrosine kinase and subsequent activation of downstream signalling pathways such as PI3K/AKT, MAPK/ERK and STAT5.

Figure 2. Schematic representation of the FLT3 receptor with bound FLT3 ligand (FL).

Legend: The figure depicts the FLT3 receptor components and indicates the sites of the two most common FLT3 mutations in AML: ITD and TKD mutations.

Abbreviations: FLT3= FMS-like tyrosine 3; TK= tyrosine kinase; ITD= internal tandem duplication; TKD= tyrosine kinase domain

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Although it is recognised that FLT3/ITD mutations have a negative prognostic impact in normal karyotype AML, the impact of FLT3/TKD mutations is less clear. TKD mutations are present in 5.8% to 7.7% of AML patients with normal karyotype66’53’67’18 and involve the activation loop in the second part of the kinase domain. They consist of point mutations which results in a constitutive activation of the FLT3 receptor and the activation of downstream signalling pathways. In 89% of cases they involve codon 835 and the most frequent substitution (49% of cases) is tyrosine for aspartic acid (D835Y).19 TKD mutations have no characteristic clinical feature and no clearly defined prognostic impact to date, nevertheless, they represent an important mechanism of resistance to TKIs, and therefore their role warrants further investigation.20’16’68’69

FLT3/ITD mutations are very heterogeneous and may vary in size and allelic load. The poor prognosis conferred by the FLT3/ITD mutation has been hypothesised to be linked to the mutation characteristics and is somewhat influenced by the association with other cytogenetic abnormalities or acquired mutations, such as insertions in NPM1.

With regards to the mutation characteristics, the parameters that might influence prognosis would be the length of the duplication and the allelic burden. FLT3 internal tandem duplications can vary between 3 and more than 400 base pairs. The insert is believed to lead to constitutive activation of the kinase domain by disturbing the auto-inhibitory interaction between the juxtamembrane domain and the activation loop which stabilises the kinase in the inactive conformation and protects the ATP binding pocket.70’55 Some believe that the longer the duplication, the worse the clinical outcome. This may be due to the fact that longer duplications will extend beyond the juxtamembrane domain and involve the first part of the kinase domain, permanently blocking the kinase domain in an active conformation and exposing the ATP binding pocket, leading to potentially increasing levels of activation.

Mutant size appears to affect complete response (CR) rate, as follows 90%, 92%, 88%, and 76% for the smallest to largest mutant size groups (15 to 27 bp, 30 to 45 bp, 48 to 63 bp, and 66 to 213 bp), respectively, but there was no significant difference noted with regards to either RR or OS related to mutant size in this study.26 However, the impact of the ITD length on outcome remains unclear, as studies analysing the importance of the mutant size have produced contradictory results, with worse survival in patients with longer ITD inserts in one study.71 Finding which was not validated in 2 further studies, suggesting a more in- depth understanding of this process is required.72’73

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The allelic ratio FLT3/ITD to wtFLT3 has also been suggested to be of prognostic significance.73’74’75 The clinical outcome seems to be influenced more by the mutant to wtFLT3 ratio rather than the presence of the FLT3/ITD per se. Both RR and 5-year OS are significantly affected by this ratio and patients with >50% FLT3/ITD burden have a dismal prognosis with a RR of 82% at 1 year and 15% OS at 5 years.26 However, due to difficulties in the polymerase chain reaction (PCR) technique to determine the ratio between mutated and wild type FLT3 accurately, this ratio cannot be utilised for prognostic assessment at present.

It has been suggested that FLT3 mutation detection may not be a good marker of minimal residual disease (MRD) in FLT3/ITD AML.76 This is due to the observed fluctuations in the mutational status of FLT3 over time in some patients and the fact that standard PCR has a limited detection sensitivity of 1 in 100 cells.77 The low sensitivity is partly due to the competition between the mutated and the wild-type FLT3 alleles,77’69 making the shorter, wild-type amplification product preferentially multiplied by PCR.78

The FLT3 mutation is not identified by standard PCR assay at certain time points in the course of the disease, because the disease burden might be lower than the detection threshold of the assay, and thus potentially explaining the changes in mutational status in some patients.79 Nevertheless, extensive research in this field over the past decade has shown promising results and despite the general belief that FLT3 status is not a good marker for MRD, several groups suggest that the identification of MRD by FLT3 status using patient-specific PCR serves as a marker of relapse.80’81’82’83 In particular, a technique called tandem duplication PCR (TD-PCR) has been able to demonstrate a correlation between the presence of the FLT3/ITD mutation and clinical outcome.79 Therefore, further research is required to consolidate FLT3/ITD mutation as a marker for MRD in AML.

1.2.3 Signalling pathways through FLT3

FLT3 mutations produce an inappropriately active kinase that transmits a ligand- independent, non-regulated growth stimulus to cells. FLT3/ITD mutations interfere with the negative regulatory function of the juxtamembrane region and lead to phosphorylation of downstream proteins directly or indirectly. A number of proteins have been reported to be phosphorylated downstream of activated FLT3 (illustrated in Figure 3).

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Figure 3. Protein phosphorylation and signal cascade downstream from activated FLT3.

Legend: The figure indicates molecules with a proposed importance in signal complex formation or downstream mediation of abnormal FLT3 signalling.

Abbreviations: GAB1=GRB2-associated-binding protein 1; GAB2=GRB2-associated-binding protein 2; GRB2=Growth factor receptor-bound protein 2; CBL= Casitas B-lineage Lymphoma; SH2= Src Homology 2; SHIP= Src homology 2 (SH2) domain containing inositol polyphosphate 5-phosphatase 1; AKT= Protein kinase B; ERK= extracellular signal-regulated ; LYN= /Yes novel; PI3K/AKT= phosphatidylinositol 3-kinase and Protein Kinase B pathway; JAK/STAT= Janus Kinase/Signal Transducer and Activator of Transcription; RAS/MAPK= Ras-Raf-MEK-ERK pathway; ACTB= Beta; MA7D1= MAP7 Domain Containing 1; LIMA= LIM Domain And Actin Binding 1; FOXO3= Forkhead Box O3; CEBPa= CCAAT enhancer-binding protein alpha; RUNX1= runt-related transcription factor 1; MLL2= mixed lineage leukemia 2; STAT5= Signal transducer and activator of transcription 5; BAD= BCL2 Associated Agonist Of Cell Death; AUP1= Ancient ubiquitous protein 1; ENO1= Enolase 1; G6PD= glucose-6-phosphate dehydrogenase; VAV= sixth letter of the Hebrew alphabet; MDC1= Mediator Of DNA Damage Checkpoint 1; GAP= GTPase-activating protein; RB1= retinoblastoma.

Examination of these proteins shows that the major signal transduction pathways leading from FLT3 activation include PI3K/AKT, RAS/MAPK and STAT5, but more work is required to elucidate the exact signalling pathway of FLT3 in leukaemia.50 (Figure 3) Several groups have reported qualitative differences in the intracellular signals transmitted by wild type and mutated receptors. Mutated receptors rely less on MAPK and AKT, but instead very strongly on constitutively activated STAT5.

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The constitutive activation of FLT3 results in alteration of gene expression as well. Several are up-regulated, whereas others are suppressed as a result. The outcome of this alteration in gene expression in FLT3 mutated cells leads to increased cell proliferation and reduced apoptosis and cell differentiation, based on the interaction of these different pathways (Figure 4).

Figure 4. Schematic summary of the FLT3 signalling pathway and altered gene regulation

Abbreviations: Proto-oncogene with serine/threonine (Pim-1, Pim-2), Suppressor of cytokine signalling (SOCS-2, SOCS-3), Ig superfamily-related, type I transmembrane glycoprotein (GP49B), Prostaglandin E synthase (PGE-R), P21 (RAC1) Activated Kinase 1 (PAK1), V-Myc Avian Myelocytomatosis Viral Oncogene Homolog (MYC), Cyclin D3 (CCND3), Dual Specificity Phosphatase 6 (DUSP6), The (IL2) receptor alpha (IL2Ralpha) and others are suppressed: CCAAT/Enhancer Binding Protein Alpha (CEBPalpha), WD Repeat Domain 87 (WDR87), B-cell lymphoma 2 (BCL2), Cyclin-dependent kinase inhibitor 1B (CDKN1B), Growth Arrest And DNA Damage Inducible Alpha (GADD45), B- cell translocation gene 2 (BTG-2), Apoptosis Associated Tyrosine Kinase (AATYK), MAF BZIP Transcription Factor B (maf-B), Retinoic Acid Receptor Gamma (RAR gamma), Maternal-Id like (MAID), RB Transcriptional Corepressor Like 2 (RB2/p130), cyclin-dependent kinase inhibitor 2A (p16ink4A), Frequently Rearranged In Advanced T-Cell Lymphomas 1 (Frat1), Regulator of G protein signalling (RGS2), Guanine nucleotide-binding protein subunit alpha (Galpha15), Alpha Tocopherol Transfer Protein (TTPA), Ecotropic Viral Integration Site 2 (Evi-2), X-Box Binding Protein 1 (Xbp1), Tumour necrosis factor (TNF).

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1.2.4 FLT3 mechanism of action

In a normal cell, FLT3 is activated by the binding of its ligand (FLT3 ligand (FL)) which results in receptor dimerisation followed by a conformational change and exposure of specific motifs with subsequent activation of the tyrosine kinase domain. This leads to receptor phosphorylation and opening of the docking sites for the signal transducing effector molecules. The activated FLT3 transduces signals through phosphorylation of cytoplasmic proteins and activates several downstream signalling pathways (RAS, RAF, MAPK, PI3K). FLT3/ITD signal differs from the wild-type FLT3 signal, and this is believed to play a role in the maturation arrest encountered in AML.

In mutated FLT3, the receptors dimerise in a ligand-independent manner, resulting in the auto phosphorylation of the receptor and constitutive activation of the tyrosine kinase domain. Some believe that the potential mechanism of constitutive activation occurs through elongation or shortening of the juxtamembrane domain (JM).84 The JM domain plays an auto-inhibitory role, maintaining the kinase in an inactive conformation (Figure 5)

JM-B (binding) is almost buried in the catalytic centre of the kinase, close to the N-terminal hinge of the activation loop. When JM-B is in the resting state, the activation loop is closed and cannot open to allow adenosine triphosphate (ATP) or protein substrates to bind, which means JM-B stabilises the inactive kinase conformation of FLT3. ITD mutations occur in JM-Z (zipper/linker peptide segment) which, in turn, maintains the JM-S (switch motif) in the correct position. When the position of JM-S is disturbed, JM-B is destabilised and the activation loop opens with constitutive activation of the tyrosine kinase16 (Figure 5). This constitutive activation leads to cytokine-independent growth and resistance to radiation- induced apoptosis in 32D-FLT3/ITD cells. 85’86

Nevertheless, murine models have demonstrated that FLT3 mutations are not sufficient to induce leukaemia alone87 and additional cooperating mutations are required for leukaemogenesis.88 However, it is still unknown which mutations and/or signalling pathways are required to collaborate with FLT3/ITD in promoting AML.

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Figure 5. Representation of the juxtamembrane domain configuration of FLT3.

Legend: The figure provides an overview of the effects on the interaction of the sub-components in FLT3 mutations

Abbreviations: JM-Z=juxtamembrane zipper ; JM-S= juxtamembrane switch; JM-B= juxtamembrane binding; ITD= internal tandem duplication

1.2.5 FL background

FLT3 ligand (FL) is a haematopoietic cytokine, structurally homologous to (SCF) and colony stimulating factor 1 (CSF-1). play important regulatory roles in through extracellular signal-transduction affecting cell survival, proliferation, differentiation and maturation.89

Its receptor (FLT3 receptor) is often overexpressed or mutated in leukaemia. FLT3 belongs to the class III receptor tyrosine kinase group of receptors, which also includes the platelet- derived growth factor receptor (PDGF) and c-, the receptor for Stem Cell Factor (SCF). FLT3 was found to be expressed specifically by early haematopoietic progenitors with stem cell activity, but not by mature blood cell populations, suggesting a potential role in haematopoiesis.90’91 Murine FL was cloned in 1993, and soon after the human FL was cloned and characterized as a transmembrane protein that can be secreted. When bound to its receptor (Flt3), it was found to stimulate the proliferation of FLT3+ bone marrow and foetal liver progenitors.92’93

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The cloning of FL allowed further in-depth investigation of its function, specifically its role in the growth and differentiation of haematopoietic progenitors in vitro. Several early studies indicated that FL had a limited effect on the growth of haematopoietic progenitors when used alone, but demonstrated a potent synergy with other haematopoietic cytokines, such as stem cell factor (SCF), interleukin 3 (IL-3), IL-6, Granulocyte-Macrophage Colony stimulating Factor (GM-CSF), Granulocyte Colony Stimulating Factor (G-CSF) and IL- 11, in promoting the generation of primarily myeloid cell colonies.94’95’96’97’98’99

In addition, FL was shown to significantly enhance the in vitro generation of B cells, mainly in combination with the cytokines SCF and IL-7.98’100’101’102 However, there was no notable effect of FL in promoting the in vitro generation of cells of the erythroid97 or megakaryocyte lineages.94 A similar result emerged from studies using human haematopoietic progenitors and the synergistic effect of FL with other haematopoietic cytokines was a clear conclusion from these experiments.95’103’99

Further understanding of the role of FL came from knock-out mouse models with FL-/- and FLT3-/-. This demonstrated a reduction in lymphoid and myeloid progenitors. FLT3- /- mice models demonstrated maintained haematopoiesis with a marked reduction in early progenitors and defective repopulation capacity of FLT3-/- bone marrow when transplanted into irradiated hosts.104 In contrast, mouse models with FL-/- showed an overall reduction in leukocyte generation, especially affecting B cell progenitors, natural- killer cells (NK) and dendritic cells (DC).105 The differences observed between FLT3-/- and FL-/- mice could indicate the existence of another FL receptor or simply reflect the differences between mouse strains. Subsequent analysis of mice lacking FLT3 signalling showed that apart from committed B cell progenitors, FL is important for the generation and/or maintenance of their uncommitted precursors, such as CLP (Common Lymphoid Progenitors)106 , EPLM (Early Progenitors with Lymphoid and Myeloid potential)107 , and early multi-potent progenitors (MPP)108’109 as all these populations express FLT3.110’111

These in vivo studies showed that active FLT3 signalling is not essential for haematopoiesis, however they have highlighted its importance during several stages of cell development. This data suggests potential FLT3 expression by HSC and together with the emerging view of heterogeneity within HSC112’113’114 support the suggestion that lineage commitment might occur earlier in cell development than originally thought. FLT3 expression is heterogeneous amongst HSC and there is clear association with the lymphoid 31 and myeloid pathways, therefore FL is believed to have a functional role in promoting the differentiation of certain progenitors.115

Knock-out mouse models (FL-/FLT3-) show reduction in early lymphoid and myeloid progenitors. This might suggest that FL has a proliferative and/or survival role on Flt3+ progenitors. Alternatively, it might reflect that FL has a differentiating factor function, since hematopoietic cytokines can promote the generation of different lineages by permissive action (selective expansion of receptor-positive lineages through promotion of their proliferation and/or survival), or by instructive action (lineage-specific activation).116’117

The generation of transgenic mouse models that express human FL demonstrated that these mice have a marked expansion of myeloid and lymphoid lineages with a reduction in erythroid and megakaryocytic lines. The negative effect of FL overexpression on the erythroid and megakaryocytic lines could suggest an instructive action of FL, promoting differentiation towards lympho-myeloid development.115 These findings, together with the data on FLT3 expression by HSC118 suggest that identifying the exact stage when FL exerts its instructive action will help elucidate its mechanism of action.

1.2.6 FLT3 and impact on AML behaviour

FLT3/ITD mutations are more commonly found in de novo rather than secondary AML cases119’51. Nevertheless, AML patients who do not have a FLT3 mutation at diagnosis, may acquire it at time of relapse.120 FLT3 mutations have also been identified in myelodysplastic syndromes (MDS) in about 3-5% of newly diagnosed patients, however these mutations sometimes appear when the disease progresses to AML, indicating a potentially late role in leukaemogenesis in this case.121 In the clinical setting, FLT3/ITD AML is associated with a high white cell count, high percentage of peripheral blood and bone marrow blasts and in 65-70% of cases is associated with a normal karyotype. It has no real negative impact on complete remission rates (CR) but increases the relapse risk (RR) and therefore predicts a poor overall survival (OS). FLT3/TKD associates the same clinical feature, but the impact on prognosis is less clear.122

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As mentioned previously, FLT3/ITD mutations may vary in length, ranging from 3 to more than 400 base pairs. Longer mutations would imply that the duplicated segment extends into the first kinase domain of FLT3. These kinase domain insertions may result in different biological effects and it has been suggested they would confer a worse prognosis.27 It remains unclear whether the length of the duplication would impact on the efficacy of the TKIs.27’123’124’125

FLT3/TKD mutations, on the other hand, involve the activation loop in the kinase domain, most frequently due to a substitution of tyrosine for aspartic acid at codon 835 (D835Y), although several other variants have been reported. FLT3/TKD mutations are less common and do not appear to have the same prognostic impact. However, they are relevant in the context of treatment with FLT3 TKIs, as most of the FLT3 inhibitors have little or no activity against these mutations. It has also been hypothesised that FLT3/TKD mutations occurring in the presence of a pre-existing FLT3/ITD mutation are a common mechanism of resistance to monotherapy with TKIs, making them an interesting target for further investigation.19

1.3 FLT3 TKIs overview

1.3.1 History

Tyrosine kinase inhibitors (TKIs) were designed to disrupt the oncogenic receptor tyrosine kinase (RTK) signalling, with multiple applications in solid tumours and haematological malignancies alike. The mode of action involves competitive inhibition of ATP in the of RTKs, thus preventing phosphorylation and activation of downstream substrates.

The first-generation FLT3 inhibitors, such as sunitinib (SU11248), (BAY 43- 9006), midostaurin (PKC412), and lestaurtinib (CEP-701), were TKIs originally developed to inhibit a variety of RTKs, mostly for use in solid tumours. They were incidentally found to have activity against FLT3 as well, and therefore, due to this non-specific inhibition and off-target effect, they often induce significant toxicity. Newer agents, such as quizartinib, crenolanib, gilteritinib, also known as second- or next-generation inhibitors, have been specifically designed to target FLT3/ITD in AML, but nevertheless, some residual inhibitory activity against other receptor tyrosine kinases in the same family remains.126

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TKIs that are direct inhibitors of FLT3 act via competitive inhibition of ATP-binding sites in the FLT3 receptor kinase domain (KD). The variations in conformational state (inactive versus active) of the FLT3 KD have divided the FLT3 inhibitors into different types. Most FLT3 inhibitors such as Quizartinib, Sorafenib and midostaurin target the inactive conformation of the kinase domain and are classed as Type II inhibitors. The next- generation inhibitors such as crenolanib, target both the active and inactive conformation and are type I inhibitors.123’127

Many factors can influence the response to TKI therapy. The type of FLT3 mutation is very important, as ITD mutations respond better to inhibition in general. ITD mutations can be heterogeneous though, and there is a lot of controversy regarding the importance of the duplication length itself, as discussed previously. The longer the duplication, the more likely it is to involve the kinase domain and some groups believe this could have an impact on the response to treatment. Moreover, it is generally believed that duplications involving the KD confer an overall poorer prognosis.49

TKD mutations, on the other hand, are less common in AML. These are point mutations in the tyrosine kinase domain, most commonly affecting the activation loop at residue aspartate D835, but several variants involving adjacent residues have been reported. Overall, the prognostic impact of TKD mutations is unclear so far, but they are believed to be an adaptive resistance mechanism in TKI monotherapy. This is important as most of the TKI molecules have no activity against TKD mutations.

It has also been noted that the FLT3 inhibitors have less activity against wild-type FLT3. An over-expression of the wild-type receptor, which is sometimes noted in AML and considered to be another mechanism of constitutive activation, would reduce the response to TKI molecules.128 The type of FLT3 mutation seems to condition the response to TKI therapy, however, the disease characteristics, such as de novo versus relapsed AML or mutant to wild-type allelic burden ratio, might also play a significant role.129

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1.3.2 Clinical trials of FLT3 TKIs in monotherapy

Several small molecules have been developed over recent years, aimed to target the FLT3 kinase, in an attempt to improve clinical outcomes in AML. The characteristics of these TKIs are summarised in Table 8 and the clinical trial results involving them are summarised in Table 9. The focus will be on Quizartininb, as the TKI selected for the experimental work presented here.

Table 8. Summary of available FLT3 inhibitors and overview of their activity spectra. Name Initial name Type Activity

Midostaurin PKC412 Type II PKC-α, VEGFR, KIT, PDGFR, FLT3 ITD and TKD

Lestaurtinib CEP701 - JAK2, TRKA/B/C, FLT ITD and TKD

Sorafenib BAY-43-9006 Type II RAF, VEGFR, KIT, BRAF, FLT3 mostly ITD

Semaxanib SU5416 - VEGFR, PDGFRβ, KIT

Sunitinib SU11248 - PDGFRβ, KIT, FLT3 ITD and TKD and even wt

Tandutinib MLN-518 - Selective to type III RTKs

KW2449 - - Multi-target inhibitor of FLT3

Quizartinib AC220 Type II KIT, PDGFRα, PDGFRβ, RET, FLT3 ITD and wt

Crenolanib CP-868-596 Type I PDGFRα and β, FLT3 ITD and TKD

Ponatinib AP24534 - KIT, FGFR1, Abl, PDGFRα, FLT3 ITD

Gilteritinib ASP2215 - FLT3 ITD and TKD, AXL, LTK and ALK

Legend: Note that most inhibitors with the exception of Midostaurin, Lestaurtinib, Sunitinib, Crenolanib and Gilteritinib, do not have activity against the TKD mutation. Type I inhibitors (such as Crenolanib) target both the active and inactive conformation of the TK domain, whereas Type II inhibitors ( such as Quizartinib, Sorafenib and Midostaurin) target the inactive conformation of the TKD.

Abbreviations: PKCa= Protein kinase C alpha; VEGFR= vascular endothelial growth factor; KIT= mast/stem cell growth factor receptor; PDGFR= Platelet-derived growth factor receptors; FLT3 ITD= FMS-like tyrosine kinase internal tandem duplication; FLT3 TKD= FMS-like tyrosine kinase tyrosine kinase domain; JAK2= Janus Kinase; TRK A/ B/ C= Tropomyosin receptor kinase A/ B/ C; RAF= Rapidly Accelerated Fibrosarcoma; BRAF= B- Rapidly Accelerated Fibrosarcoma

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Table 9. Clinical trial results of TKIs in mono- or combination therapy in AML.

Name Study details Treatment Results

Midostaurin Phase II Oral, 75 mg three times daily n=20, PR=1, clinical benefit Stone et al.138 Rel/ref AML or HR MDS or 7/20, 50% reduction in PB unfit for intensive chemo blast count 14/20. Fischer et al.139 Phase IIB Oral, randomised to 50 or 100 mg twice N=95 (60 wt, 35 FLT3 AML or MDS with wt or daily mutated), 50% reduction in mutated FLT3 PB/BM blasts 25/35 FLT3 mutated vs 25/60 wt Lestaurtinib Phase I/II Oral, 40 - 80 mg twice daily n=17, CR=1, 50% reduction in Smith et al.140 Rel/ref or HR FLT3 AML PB blasts 5/17 Knapper et al.135 Phase II Oral, 60-80 mg twice daily n=29, clinical benefit 8/27 Untreated AML patients, unfit evaluable patients (3 FLT3 independent of FLT3 status mutated, 5 wtFLT3), no CR/PR achieved Sorafenib Phase I Oral, 200-400 mg twice daily n=16, 6/6 FLT3/ITD patients Zhang et al.141 Rel/ref AML achieved a clinical response Crump et al.142 Phase I Oral, 100-400 mg twice daily N=42, CR=1, no other Rel/ref AML, elderly MDS or responses secondary AML Metzelder et al.143 Compassionate use in rel/ref Oral, 100-400 mg twice daily N=6, HR/BMR=4/6 with 1/4 FLT3/ITD AML pre/post =CR, 1/6 CR, 1/6 HR HSCT Sharma et al.144 Relapsed FLT3/ITD AML Monotherapy (n=8) 400-600 mg or N=16, PR=3, 50% reduction in following HSCT with chemotherapy (n=8) 400 mg twice PB blasts in 3/16, no OS daily difference between mono/combination therapy Metzelder et al.145 FLT3/ITD AML patients in 400 mg twice daily N=65, HR=54, PR=10, only 1 CR or relapsed post HSCT non-responder Phase II 145mg/m2 intravenous twice weekly N=55, PR=3, HI=1, BMR=4, Giles et al.146 Rel/ref AML/MDS stable disease=40, progressive independent of FLT3 status disease=13 Fiedler et al.147 Phase II 145mg/m2 intravenous twice weekly N=42 (evaluable n=25) PR=7, Refractory c-KIT positive MR=1, no response in the 7 AML or unfit for FLT3/ITD patients chemotherapy Sunitinib Phase I Oral, 50-350 mg single dose N=29. Phosphorylation O’Farrell et al.136 Rel/ref AML or unfit for other inhibition in all 5 /29 FLT3 treatments mutated cases Fiedler et al.137 Phase I Oral, 50 mg daily N=16. 3/5 FLT3/ITD patients Rel/ref AML or unfit for showed reduction of FLT3 conventional chemotherapy phosphorylation in PB Tandutinib Phase I Oral, 50-700 mg twice daily N=40, no PR/CR. 2/8 patients DeAngelo et al.148 Rel/ref AML or unfit for with FLT3/ITD had >50% conventional chemotherapy reduction in PB blasts KW2449 Phase I Oral, 25-500 mg twice daily (7 dose 5/11 patients with FLT3/ITD Pratz et al.149 Rel/ref AML, ALL or CML levels) had a 50% reduction in PB not respoding to 3+3 design blasts / Quizartinib Phase I Oral, 12-450 mg daily N=76, PR=13, CR=10, 10/18 Cortes et al.130 Rel/ref AML or elderly 3+3 design FLT3/ITD patients achieved patients unfit for conv.treatm PR/CR. NO response in FLT3/TKD Cortes et al.130 Phase II Oral, 30 or 60 mg daily (38 patients N=76, CRc=38/76 equal Rel/ref AML each arm) across both arms Burnett et al.150 Phase I Oral, 40-135 mg daily N=55, CR=33 (including all 4 Untreated AML pts >60 years 3+3 design FLT3/ITD patients) old +Ara-C/ Daunorubicin/Etoposide Levis et al.133 and Phase II Oral, 90-135 mg N=271, CRc=147 pts, median Cortes et al.130 Rel/ref AML OS=25 weeks Crenolanib Phase II Oral, 200mg/m2/day in 3 divided doses N=38(34 evaluable). Cri=4, Randhawa et al.151 Rel/ref AML with FLT3 Hi=11, BM blast clearance=1, mutations PD=7, no response=11 Phase I Oral, 30-45 mg daily N=12, (7/12 were FLT3 ITD). Shah et al.152 Rel/ref AML Cri=2, PR=1, stable disease=3, PD=2 Gilteritinib Phase I/II Oral, 20-450 mg daily N=166, CRc=67 and PR=22 in Levis et al.153 Rel/ref AML 3+3 design FLT3 mutated and CRc=3 and PR=1 FLT3 wt Abbreviations: PR=partial remission; PB=peripheral blasts; BM=bone marrow; CR=complete remission; HR=haematological remission; BMR=bone marrow response; MR=morphological remission; Cri=incomplete CR; Hi=incomplete HR CRc= composite CR; PD=progressive disease 36

1.3.2.1 Quizartinib (AC220)

Quizartinib is a type II, second generation TKI which exhibits inhibitory activity against KIT, PDGFRα and β, RET and most importantly, FLT3/ITD as well as wtFLT3. It has an oral administration and has proven to be a potent and selective FLT3 inhibitor, targeting the inactive conformation of the kinase domain. (Figure 6).

Figure 6. Representation of a FLT3 molecule and the potential mechanism of inhibition through TKI.

Legend: The figure shows the competitive binding of a TKI molecule and an ATP molecule, both competing for the same , presumed in the tyrosine kinase insert.

Abbreviations: TK= tyrosine kinase; ATP= adenosine triphosphate; TKI= tyrosine kinase inhibitor

It has a good bioavailability and with a half-life of more than 24 hours it ensures a more continuous FLT3 inhibition. Quizartinib has been trialled in monotherapy in a phase I study in 76 relapsed or refractory AML patients or elderly patients unfit for conventional treatment at oral doses ranging from 12 to 450 mg daily and achieved PR or CR in 10/18 FLT3/ITD patients and showed no response in patients with the TKD mutation.130 The second phase I trial looked at 55 previously untreated AML patients over 60 years old, at oral doses ranging from 40 to 135 mg daily in combination with Ara-

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C/Daunorubicin/Etoposide and achieved a CR in 33 patients, including all 4 patients with the FLT3/ITD mutation.131

Two phase II trials looked at Quizartinib in monotherapy in refractory or relapsed AML patients. The first one analysed 76 patients at 2 different doses of 30 or 60 mg daily and achieved a CRc of 38/76 equal in both arms.132 The second one with 271 patients used doses ranging from 90 to 135 mg daily and achieved a CRc in 147/271 patients.130 Quizartinib has been trialled in phase I and phase II studies at different doses and regimes (mono- or combination therapy) as detailed above and showed inhibition of FLT3 phosphorylation at all doses tested. It showed promising results in terms of CR and OS and the phase III trial comparing Quizartinib monotherapy to salvage chemotherapy in relapsed/refractory AML (NCT02039726) is underway.

1.3.2.2 Lestaurtinib (CEP-701)

Lestaurtinib is an indolocarbazole inhibitor, not exclusive to FLT3, which exhibits activity against both ITD and TKD mutations. In preclinical studies, it demonstrated inhibition properties against wild-type and mutant FLT3 in vitro with a high degree of correlation between FLT3 inhibition and cytotoxicity.133’134

An initial phase 1/2 study which used Lestaurtinib in 14 patients with refractory, relapsed or high risk FLT3 mutated AML, indicated that the drug was well-tolerated. Five patients experienced a >50% reduction in peripheral blasts and one patient achieved a CR. This study was followed-up with a subsequent phase 2 study in untreated older AML patients, independent of the FLT3 mutational status, considered unfit for conventional chemotherapy.135 Lestaurtinib was administered orally at a dose of 60 mg twice daily and then escalated to 80 mg with good tolerance. Responses were limited and varied between haematological response and CR. The clinical responses correlated in both studies with sustained FLT3 inhibition as assessed by PIA assay.135

1.3.2.3 Sunitinib (SU11248)

Sunitinib is an oral multi-targeted kinase inhibitor which has displayed some activity against FLT3/TKD and an increased activity against wtFLT3, compared to other TKIs. Two phase 1 trials were conducted with different dosing regimens, the first used doses higher than 200 mg, whereas the second found 50 mg daily to be the maximum tolerated dose.

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They both showed some evidence of clinical activity, but the responses were short lived (4-16 weeks).136’137

1.3.3 FLT3-TKIs in combination with chemotherapy

This model looks at adding a i.e. FLT3 TKI to standard chemotherapy regimens and aims to understand whether this combination has an impact on outcome in AML patients.

Several trials have looked at this combination but none of the results have been sufficiently promising to make this combination a standard of care in AML patients with FLT3 mutations (Table 9). Nevertheless, continued work in this direction is underway and several trials supporting this combination are ongoing. The interim analysis of a phase I/II trial of Quizartinib in combination with azacitidine or cytarabine (NCT01892371) reported an overall response rate of 82% in FLT3/ITD AML, MDS or chronic myelomonocytic leukaemia154 and the phase III trial of gilteritinib versus salvage chemotherapy in relapsed/refractory AML with FLT3 mutation (EudraCT 2015-000140-42) is ongoing.

1.3.4 FLT3-TKIs in combination with other small molecules

Despite promising results in vitro, FLT3 TKIs in monotherapy do not seem sufficient to change the course of the disease or the outcome. This is due to several potential mechanisms. One mechanism is the simultaneous activation of other survival pathways such as MAPK, JAK/STAT, and PI3K/AKT, therefore the thought of inhibiting multiple pathways at the same time arose.155

There are several possible combinations that have demonstrated synergistic effects in vitro, such as the mTOR inhibitor rapamycin or the dual pyruvate dehydrogenase (lipoamide) kinase isozyme 1/PI3K inhibitor BAG956 with midostaurin and the mTOR-inhibitor RAD001 or the MAPK-ERK1/2 inhibitor AZD6244 combined with sunitinib, which are currently being investigated in clinical trials.156’157’158’159 Some of these combinations have reached phase I trials, such as the mTOR inhibitor RAD001 in combination with midostaurin (ClinicalTrials.gov identifier, NCT00819546). In vitro synergism has also been demonstrated using combinations with the heat shock protein-90 inhibitor 17-AAG and the histone deacetylases inhibitor MS-275. These initial results seem promising, but further investigation into the toxicity and optimal combination of these molecules is required in order to validate their role in the treatment of FLT3 mutated AML.160’161

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1.3.5 FLT3 TKIs and role post stem cell transplantation

FLT3 TKIs have also been considered as maintenance therapy after HSCT. FLT3/ITD mutation increases the relapse risk in AML patients, even after HSCT, therefore the role of FLT3 TKIs has been considered as maintenance therapy in the post-HSCT setting. Quizartinib entered a phase I study as maintenance therapy in FLT3 mutated AML patients in CR after allogeneic HSCT. Two different daily doses of 40 mg and 60 mg were tested in 28-day cycles and only 1/13 patients developed a relapse. This study did not test higher doses, but 60 mg daily was the recommended dose.162

Another phase I study investigated the role of Sorafenib as maintenance therapy in the post- HSCT setting. Twenty-two FLT3 mutated AML patients post-HSCT (12 myeloablative and 10 reduced intensity conditionings) were entered in the study. Sixteen were in first CR, three in second CR and three had refractory disease at time of transplantation. The drug was initiated between day 45 and 120 post-HSCT and continued for twelve 28-day cycles at a maximum tolerated dose of 400 mg twice daily. After a median follow-up of 14.5 months, the results were promising with a 1-year progression-free survival of 84% and OS of 95%.163 These results, however, require validation in larger randomised controlled studies. A retrospective analysis of 6 post allo-HSCT patients164 suggested that Sorafenib in addition to its action of FLT3 inhibitor, also possesses an immunomodulatory role, which synergises with the graft-versus-leukaemia effect.145 Two phase I trials of Sorafenib in the peri-transplant setting (NCT01398501 and NCT01578109) are currently underway.

1.3.6 Molecular mechanisms of resistance to TKIs

Despite initial anticipation with regards to efficacy, the FLT3 TKIs have not demonstrated benefit in the overall disease outcome in FLT3 mutated AML patients. This is due to the fact that despite inhibition of phosphorylation in vitro, the effects are not always correlated with improved clinical outcome in this sub-group of patients. Another major issue observed is the transient response achieved, with subsequent development of drug resistance, especially in the context of TKI monotherapy.

It was postulated that the mechanisms of drug resistance in the case of FLT3 TKIs could be divided into extrinsic, receptor-intrinsic and cell-intrinsic (Figure 7).

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Figure 7. Schematic representation of the different types and mechanisms of resistance to FLT3 inhibitors.

Legend: Mechanisms of resistance to TKIs can be divided into extrinsic and intrinsic. Extrinsic mechanisms include drug metabolism and drug interactions. Intrinsic include receptor-related (point mutations, receptor over-expression and ITD length or insertion site and cell-related include parallel pathways, stromal factors and anti-apoptotic pathways.

Extrinsic mechanisms of resistance include drug metabolism and interactions, thus influencing the pharmacokinetics of the drug. Other factors affect the pharmacokinetics of TKIs, like protein binding, thus reducing the free levels of circulating drug. Increased levels of FLT3 ligand (FL) were also observed in successive courses of chemotherapy thus interfering with FLT3 inhibition through competitive binding. Receptor-intrinsic mechanisms of resistance include resistance-conferring point mutations, receptor over- expression and ITD length or insertion site. It has been suggested that the characteristics of the ITD may determine response to treatment. The location of the ITD in the TKD domain is associated with poor response to chemotherapy and long duplications correlate with inferior survival, probably due to the same mechanism of action, by involving the TKD.

Cell-intrinsic resistance mechanisms involve the activation of parallel pathways through stromal factors or Ras mutations, modulation of anti-apoptotic pathways and the hypothesis 165 166 of non-addicted sub-clones. ’ Ras is the prototypical member of the Ras superfamily of proteins (small GTPases) which are involved in cellular signal transduction and regulation of cell behaviour. Mutations in ras genes can lead to the production of permanently activated Ras proteins and as a result induces overactive intracellular signalling, even in

41 the absence of incoming signals. These signals result in cell growth and division, therefore 167 overactive Ras signalling can ultimately lead to cancer.

It is also believed that the bone marrow environment plays an important role in FLT3 TKI resistance, by creating a protective leukaemic niche and rendering the blasts less susceptible to therapy.168’169 This effect is seen with Quizartinib in particular, which induces apoptosis in circulating blasts, but promotes differentiation in bone marrow blasts.170 It has also been observed, in vitro, that FLT3 inhibitors are more effective in the relapse setting and when a high allelic burden is present, which might constitute yet another mechanism of resistance.129 Treatment failure to TKI therapy may be caused by primary (inherent) resistance or development of secondary (acquired) resistance after an initial response.

1.3.6.1 Primary resistance

Following phase 1 and 2 studies of FLT3 TKI monotherapy, primary resistance to therapy was suspected in 30% of AML patients with FLT3 mutation, even despite complete inhibition of FLT3 phosphorylation. In some patients, persistent activation of STAT5 and MAPK pathways was demonstrated, thus suggesting activation of compensatory survival pathways rendering the leukaemic cells FLT3/ITD independent.171 Primary resistance can be summed up in FLT3-dependent resistance when the FLT3 mutations are insensitive to the TKI used and FLT3-independent resistance when the cells are not addicted to FLT3 and activate alternative survival pathways134 (Figure 8).

1.3.6.2 Secondary resistance

Secondary resistance occurs following exposure to FLT3-TKI therapy. TKI monotherapy showed a partial and transient response in treated patients, thus potentially suggesting insufficient plasma drug levels, short plasma half-life or hepatic metabolisation, leading to secondary drug resistance.172 There are different mechanisms leading to secondary resistance, including development of resistance mutations in the ATP-binding pocket of FLT3, autocrine FL stimulation, FLT3 overexpression and activation of alternative pathways, rendering the FLT3 mutated cells independent of FLT3 signalling. FLT3 TKI- resistant cells demonstrated a common feature in the dysregulation/overexpression of anti- apoptotic proteins, such as myeloid leukaemia cell differentiation protein (MCL1), survivin and B-cell lymphoma 2 (BCL2), suggesting that these signalling proteins would potentially make ideal targets in resistant leukaemia.173’174

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Primary Resistance

FLT3 - Dependent FLT3 - Independent

Secondary Resistance

Resistance mutations Activation of FL Stimulation FLT3 over expression in the ATP-binding site alternative pathways

Figure 8. Detailed representation of the potential mechanisms of resistance to FLT3 inhibitors

Legend: Resistance mechanisms can be divided into primary and secondary resistance. Primary resistance can be FLT3-dependent or independent; secondary resistance can be attributed to FL stimulation, mutations in the ATP-binding site, FLT3 overexpression or activation of alternative pathways.

1.3.7 Signalling pathways related to FLT3

The FLT3 ligand (FL) is a signalling molecule that acts through phosphorylation of target proteins. Phosphorylation is a reversible modification of proteins – an amino acid residue is phosphorylated by a protein kinase through the addition of a phosphate group by covalent binding. Phosphorylation alters the structural conformation of that protein, causing its activation, deactivation or modifying its function. The process is reversed by enzymatic de-phosphorylation (catalysed by protein ). The balance between protein kinases and phosphatases therefore allows them to regulate the function of proteins. Abnormal protein phosphorylation is implicated in numerous pathologies, notably cancer. The amino acids most commonly phosphorylated are serine, threonine, and tyrosine, playing important roles in signalling pathways. While tyrosine phosphorylation is found in relatively low abundance, it is well studied due to the ease of purification of phospho- tyrosine using antibodies.

Receptor tyrosine kinases are a family of cell surface receptors that are involved in the transduction of extracellular signals following the binding of hormones, growth factors, or cytokines. In many cases, the binding of a ligand to a monomeric receptor tyrosine kinase promotes the interaction between two monomers to form a dimer. The newly-formed dimer

43 undergoes phosphorylation of key tyrosine residues resulting in the activation of the receptor. The receptor then activates downstream signalling pathways through further phosphorylation or other enzymatic activity through interactions with downstream effector or adaptor proteins.

Recent advances in phospho-proteomic identification has resulted in the discovery of countless phosphorylation sites in proteins. Phosphorylation of a protein can change the function or localisation of that protein, therefore understanding the "state" of a cell requires knowing the phosphorylation state of its proteins.

It is recognised that FLT3 signal generation primarily induces signalling in three separate but related pathways: JAK/STAT pathway; MAPK/ERK pathway; PI3K/AKT pathway. These pathways are therefore outlined in the sections that follow.

1.3.7.1 JAK/STAT pathway

Members of the signal transducer and activator of transcription (STAT) are intracellular transcription factors that mediate several aspects of cellular immunity, proliferation, apoptosis and differentiation. Gene knockout studies have provided evidence that STAT proteins are involved in the development and function of the and play a role in maintaining immune tolerance and tumour surveillance. There are seven mammalian STAT family members that have been identified: STAT1, STAT2, STAT3, STAT4, STAT5 (STAT5A and STAT5B), and STAT6. They are primarily activated by membrane receptor-associated Janus kinases (JAK). STAT proteins can also be phosphorylated directly by receptor tyrosine kinases, such as receptor (EGFR) or by non-receptor tyrosine kinases (cytoplasmic) such as c-src.

The JAK-STAT signalling pathway (Figure 9) transmits information from extracellular signals to the nucleus resulting in DNA transcription and expression of genes involved in immunity, proliferation, differentiation, apoptosis and oncogenesis. Dysregulation of this pathway is frequently observed in primary tumours and leads to increased angiogenesis, enhancing the survival of tumours and immunosuppression.

The JAK-STAT signalling cascade consists of three main components: a cell surface receptor, a Janus kinase (JAK) and two Signal Transducer and Activator of Transcription

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(STAT) proteins. Disruption or dysregulation in the JAK-STAT function can result in immune deficiency syndromes and cancers.

The JAK-STAT pathway is negatively regulated through protein tyrosine phosphatases which remove phosphates from cytokine receptors and activated STATs175 but also through suppressors of cytokine signalling (SOCS) which can inhibit STAT phosphorylation by binding and inhibiting JAKs or by competing with STATs for phosphor-tyrosine binding sites on cytokine receptors.176

STATs are also negatively regulated by protein inhibitors of activated STAT (PIAS), which act directly in the nucleus,177 for example, PIAS1 and PIAS3 inhibit transcriptional activation by STAT1 and STAT3, respectively by binding and blocking access to the DNA sequences they recognize.

Figure 9. JAK/STAT signalling pathway showing a step-wise process activation.

Pathway image adapted from Douglas A. Harrison, The JAK/STAT Pathway. Cold Spring Harb Perspect Biol 2012;4:a011205

Explanation: 1) binds ligand; 2) receptor dimerization activates JAK leading to the phosphorylation of the receptor, creating binding sites for proteins possessing SH2 domains; 3) STATs containing SH2 domains bind to the phosphorylated receptor; 4) JAK phosphorylates STAT and a STAT hetero- or homo- dimer is formed, travels to the nucleus, binds DNA, inducing transcription of target genes.

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STAT5 contains two similar proteins (STAT5A and STAT5B), which although are very similar at the amino acid level, are encoded by separate genes.178 STAT5 proteins are involved in signalling and gene expression mediation.179 Aberrant STAT5 activity is associated with several cancers175 and research into mechanisms to silence this aberrant activity is ongoing.176

In the nucleus, the STAT5 dimers induce transcription of specific genes and are known to upregulate expression of genes involved in cell differentiation and proliferation, apoptosis and inflammation. Activated STAT5 dimers are short-lived and undergo deactivation rapidly, either directly by removing a phosphate group using protein inhibitors of activated STAT (PIAS) or indirectly by inhibiting the cytokine signalling.180

1.3.7.2 The MAPK/ERK pathway

The MAPK/ERK pathway (also known as the Ras-Raf-MEK-ERK pathway) represents a group of intracellular proteins that transmit a signal from a cell surface receptor, resulting in a range of functional responses that ultimately include transcription of nuclear DNA and subsequent protein biosynthesis.181 MAPK (-activated protein kinases) was originally called ERK (extracellular signal-regulated kinases) and transmits signals by adding phosphate groups to a neighbouring protein, acting as an "on" or "off" switch. Mutations block the switch in the “on” or “off” position, an essential step in carcinogenesis. However, the interactions of MAPK are considerable and include many inter-related pathways182 (Figure 10).

Briefly, when the ligand binds a membrane receptor such as EGFR, small GTPase intermediaries are activated and caused to switch from GDP-bound (inactive) to GTP- bound (active) form. This requires the action of docking proteins (e.g. GRB2) that form molecular complexes (e.g. the GRB2-SOS complex) which promote the removal of GDP from Ras proteins (particularly H-Ras or K-Ras), allowing them to bind GTP and become active. This in turn causes the activation of MAP3K (Raf), which activates MAP2K then MAPK. MAPK now acts on transcription factors (e.g. Myc). The activated Ras activates then promotes RAF kinase to phosphorylate and activates MEK1 and MEK2 allowing them to activate MAPK.183,184 It is believed that FLT3 follows a similar activation process.

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MAPK has significant effects on the regulation of translation and transcription: MAPK activation is recognised to alter the translation of mRNA to proteins by phosphorylating the 40S ribosomal protein S6 kinase (RSK) resulting in the phosphorylation of ribosomal protein S6 by the intermediary RSK.185 Additionally, MAPK regulates several transcription factors through the action of MYC or FOS causing altered transcription of genes that are important for the cell cycle.

Figure 10. Diagram of the interactions of the MAPK pathway.

Pathway image from Deborah. K Morrison, MAP Kinase Pathways. Cold Spring Harb Perspect Biol. 2012 Nov; 4(11)

Explanation: When ligand binds a membrane receptor such as EGFR, small GTPase intermediaries are activated and caused to switch from GDP-bound (inactive) to GTP-bound (active) form. This requires the action of docking proteins (e.g. GRB2) that form molecular complexes (e.g. the GRB2-SOS complex) which promote the removal of GDP from Ras proteins (particularly H-Ras or K-Ras), allowing them to bind GTP and become active. This in turn causes the activation of MAP3K (Raf), which activates MAP2K then MAPK. MAPK now acts on transcription factors (e.g. Myc). The activated Ras activates then promotes RAF kinase to phosphorylate and activates MEK1 and MEK2 allowing them to activate MAPK

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The MAPK pathway can also promote cell growth and proliferation through sustained activity that activates genes that induce cell cycle entry and suppress negative cell cycle regulation.186 Important targets include the -Cdk4/6 complex, which prepares cells to enter S-phase in response to mitogen and contributes to hyper-phosphorylation and destabilisation of the retinoblastoma protein (Rb) preventing its inhibitory effects against S-phase entry genes such as Cyclin E and Cyclin A2. MAPK activation downstream of Ras signalling is sufficient to allow cells to progress to S-phase.187,188

MAPK can also affect cell proliferation independently of effects on gene transcription - recent studies have shown that signalling by ERK kinase causes the activation of p53 to determine whether the cells formed following mitosis re-enter cell cycle or become quiescent. Chemical perturbations using inhibitors of ERK signalling may cause cells primarily to enter G0.

1.3.7.3 PI3K/AKT pathway

PI3K-Akt Pathway is an intracellular signal transduction pathway that promotes metabolism, proliferation, cell survival, growth and angiogenesis in response to extracellular signals. This is mediated through serine and/or threonine phosphorylation of a range of downstream substrates. The PI3K-Akt pathway has many downstream effects, hence regulation of this pathway (Figure 11) is essential.

The key molecules involved in this pathway are receptor tyrosine kinase (RTKs), phosphatidylinositol 3-kinase (PI3K), phosphatidylinositol-4,5-bisphosphate (PIP2), phosphatidylinositol-3,4,5-bisphosphate (PIP3) and AKT/protein kinase B.189, 190AKT, also known as protein kinase B, is a serine/threonine-specific protein kinase that plays a key role in multiple cellular processes. This pathway becomes activated through the production of phosphatidylinositol 3,4,5 triphosphates by phosphoinositide 3-kinase (PI3K).

PI3K is activated following receptor engagement causing the phosphorylation and activation of AKT on Thr308 and Ser473 at the cell membrane. Once activated, AKT regulates the function via phosphorylation activation or suppression of a broad array of proteins involved in cell growth, proliferation, motility, adhesion, neovascularization, and cell death. Phosphorylation by AKT can be inhibitory or stimulatory, either suppressing or 48 enhancing the activity of target proteins. Negative regulation of AKT is induced through the action of PTEN.191

Figure 11. Diagram of the PI3K/AKT pathway.

Pathway image from Debashis Sarker, Alison H.M. Reid, Timothy A. Yap, and Johann S. de Bono. Targeting the PI3K/AKT Pathway for the Treatment of . Clin Cancer Res 2009;15(15) August 1, 2009

Explanation: Key players in the PI3K/AKT/mTOR are phosphatidylinositol 3-kinase (PI3K), phosphatidylinositol-4,5-bisphosphate (PIP2), phosphatidylinositol-3,4,5-bisphosphate (PIP3) and AKT/protein kinase B. This pathway becomes activated through the production of phosphatidylinositol 3,4,5 triphosphates by phosphoinositide 3-kinase (PI3K). PI3K is activated following receptor engagement causing the phosphorylation and activation of AKT on Thr308 and Ser473 at the cell membrane.

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The PI3K/AKT/mTOR pathway plays a major role in regulating the cell cycle including cell growth, but also metabolism and survival. Dysregulation of the PI3K/AKT may occur through mutations that affect intrinsic kinase activity of PI3K or of AKT or as a downstream consequence of an abnormally activated kinase (such as FLT3/ITD). It may also be activated through mutation of the negative regulators PTEN or 2A (PP2A).192, 193

In general, the function of PI3K-AKT signalling pathway is to stimulate cell proliferation and growth, and simultaneously inhibit cell apoptosis.194 The over-activation of this signalling pathway can over-stimulate cells and result in abnormal cell proliferation, i.e. oncogenesis. Abnormalities in the PI3K pathway are common in cancer193 and have a role in neoplastic transformation and PI3K itself is a target of mutational activation.

1.4 Mass spectrometry

Mass spectrometry (MS) is an analytical technique used to determine the molecular mass of chemical compounds, like small organic molecules (drugs, hormones, metabolites) or large biomolecules (lipids, carbohydrates, proteins).195 It employs ionisation to detect and display the ions in a sample based on their mass-to-charge ratio (m/z), basically it measures the masses within a sample. A mass spectrum is a plot of the ion signal as a function of the mass-to-charge ratio. These spectra are used to determine the masses of particles within a sample, and to elucidate the chemical structures of molecules, such as peptides or other chemical compounds.

A mass spectrometer consists of three components: an ion source, a mass analyser, and a detector (Figure 12). The ion source converts a portion of the sample into ions. There is a wide variety of ionisation techniques, depending on the phase (solid, liquid, gas) of the sample and the efficiency of various ionisation mechanisms for the unknown species. An extraction system removes the ions from the sample and targets them through the mass analyser and onto the detector. The difference in masses of the fragments allows the mass analyser to display the ions based on their mass-to-charge ratio.196 The detector measures the value of an indicator quantity and thus provides data for calculating the abundance of each ion present in the sample.

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Sample Data system

Ion source Mass analyser Detector

Vacuum system

Figure 12. Schematic representation of the components of a mass spectrometer.

Explanation: The proteins in the sample are digested to peptides and introduced in the MS. Results are displayed as spectra of the relative abundance of detected ions as a function of the mass-to-charge ratio. The molecules in the sample can be identified by correlating known masses to the identified masses or through a characteristic fragmentation pattern. The time of flight (TOF) is analysed and aminoacids (aa) are detected and a sequence of aa is generated to give a protein ID.

In a MS procedure, a sample (solid, liquid or gas) is ionised causing the molecules in the sample to form charged particles. These ions are then separated according to their mass-to- charge ratio, by accelerating them and subjecting them to an electric or magnetic field. The electric or magnetic field will influence the trajectory of the ions as they pass through the mass analyser, according to their mass-to-charge ratios, deflecting the more charged and faster-moving, lighter ions more, based on the fact that ions of the same mass-to-charge ratio will undergo the same amount of deflection.

The analyser can be used to select a narrow range of m/z or to scan through a range of m/z to catalogue the ions present. The time-of-flight (TOF) analyser uses an electric field to accelerate the ions and then measures the time they take to reach the detector.197-199 If the particles have the same charge, the kinetic energies will be identical, and their velocities will depend only on their masses. Ions with a lower mass will reach the detector first.

The ions are detected through a mechanism of detecting charged particles, such as an electron multiplier. Results are displayed as spectra of the relative abundance of detected ions as a function of the mass-to-charge ratio. The molecules in the sample can be identified by correlating known masses to the identified masses or through a characteristic fragmentation pattern.

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Mass spectrometry is an important method for the characterisation and sequencing of proteins. Tandem mass spectrometry, also known as MS/MS, involves multiple steps of mass spectrometry selection, with some form of fragmentation occurring in between the stages.200 In a tandem mass spectrometer, ions are formed in the ion source and separated by mass-to-charge ratio in the first stage of mass spectrometry (MS1). Ions of a particular mass-to-charge ratio (precursor ions) are selected and fragment ions (product ions) are created by collision-induced dissociation (CID), ion-molecule reaction, photo- dissociation, or other process. The resulting ions are then separated and detected in a second stage of mass spectrometry (MS2) (Figure 13).

The two primary methods for ionisation of whole proteins are electrospray ionisation (ESI) and matrix-assisted laser desorption/ionisation (MALDI).201, 202

MALDI (matrix-assisted laser desorption/ionization) is a technique based on the principle of laser desorption (LD) ionization which consists of irradiating low-mass organic molecules with a high-intensity laser pulse, thus forming ions that can be mass analysed. The technique underwent substantial development, and the introduction of a matrix (a small organic molecule) in LD helped by-pass the mass limitation encountered previously. A low concentration of the analyte is mixed with the matrix onto a probe or metal plate and introduced into a pulsed laser beam, producing an explosion of ions with each laser pulse. MALDI consist of three steps: formation of a “solid solution”, matrix excitation and analyte ionisation.

• Formation of a “Solid Solution”: The matrix needs to be in excess, ensuring the analyte molecules are completely isolated from each other, forming a homogenous 'solid solution', ensuring a stable desorption of the analyte. • Matrix Excitation: The laser beam is targeted at the surface of the matrix-analyte solid solution, the matrix absorbs the irradiation causing vibrational excitation and producing disintegration of the solid solution. The particles released from the surface are analyte molecules, matrix residue and salt ions. The matrix molecules evaporate and leave the free analyte in the gas-phase. • Analyte Ionisation: The ionisation reactions take place in the desorbed matrix-analyte mixture just above the surface. The matrix molecules are stabilised through proton transfer or cation attachment to the analyte.

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However, MALDI is a somewhat historical method that requires the use of a TOF mass spectrometer. One of the greatest limitations of MALDI is the low analytical sensitivity and the underrepresentation of low-mass components, which at high polydispersity results in MALDI data not being representative of the distribution.

ESI (electrospray ionization) is a technique that was developed after MALDI and was perfected around the 1960s and is based on the use of electrospray to ionise intact chemical species. However, it was not until the 1980s when ESI started to be used for the ionisation of high mass biological compounds for subsequent analysis by mass spectrometry.

The ESI source has continued to be perfected over the years, however the general principle remained basically unchanged. The analyte is introduced to the source in solution (from a syringe pump or as flow from liquid chromatography), the analyte solution passes through the electrospray needle that has a high potential difference, thus forcing the spraying of charged droplets from the needle. The droplets are charged with the same polarity as the needle and are therefore repelled from the needle towards the source sampling cone on the counter electrode. As the droplets travel between the needle tip and the cone, the solvent evaporates and the droplets start shrinking until the surface tension can no longer sustain the charge and the droplets are pulled apart. This produces smaller droplets that repeat the process as well as singly or multiply charged analyte molecules. The major disadvantage of ESI is that almost no fragmentation is produced, therefore for structural elucidation studies, tandem mass spectrometry is required, where the analyte molecules can be fragmented.

One of the main challenges with the mass spectral analysis of proteins had been that their masses fall outside the mass ranges of most mass spectrometers. Before the development of ESI, the only practical ionisation method for the analysis of biological samples was fast atom bombardment (FAB). But this technique produced mostly singly charged ions and was used in instruments with mass ranges up to m/z 8 kDa, which limited analysis greatly. The only way around this limitation was to digest the protein and analyse the digest mixture. Protein digestion is still an important technique in mass spectrometry, however, at present, it is relatively easy to obtain direct mass measurements of proteins by ESI-MS. ESI-MS is a very soft method of ionisation and has established itself as an important technique in biological studies where it is often required that non-covalent molecule- protein or protein-protein interactions are transferred into the gas-phase.

53

Two approaches are used for characterising proteins. In the first, intact proteins are ionised by either of the two techniques described above, and then introduced to a mass analyser. In the second, proteins are enzymatically digested into smaller peptides using proteases such as trypsin or pepsin. The collection of peptide products is then introduced to the mass analyser.

Figure 13. Schematic representation of the stages of tandem mass spectrometry.

Legend: ESI=electrospray ionisation; MALDI=matrix-assisted laser desorption ionisation

Explanation: The sample is introduced in the MS and ionised (most commonly via ESI or MALDI). The ions are separated according to their m/z ratio in the 1st stage of MS (MS1) and selected ions are fragmented further (commonly through collision-induced or photo-dissociation) and separated again based on the m/z ratio in the 2nd stage of MS (MS2).

When the characteristic pattern of peptides is used for the identification of the protein the method is called peptide mass fingerprinting (PMF), if the identification is performed using the sequence data determined in tandem MS analysis it is called de novo peptide sequencing.203

In mass spectrometry, data-independent acquisition (DIA) is a method of molecular structure determination.204-206 It implies that all ions within a selected m/z range are fragmented and analysed in a second stage of tandem mass spectrometry. Tandem mass spectra are acquired either by fragmenting all ions that enter the mass spectrometer at a given time (broadband DIA) or by sequentially isolating and fragmenting ranges of m/z. DIA is an alternative to data-dependent acquisition where a fixed number of precursor ions are selected and analysed by tandem mass spectrometry.

Data analysis is challenging for DIA methods as the resulting fragment ion spectra are highly multiplexed. One approach to DIA data analysis attempts to use database-based search engines used in data-dependent acquisition to search the produced multiplexed

54 spectra. A second approach is based on a targeted analysis, also known as SWATH-MS (Sequential Window Acquisition of All Theoretical Fragment Ion Mass Spectra). This approach uses targeted extraction of fragment ion traces directly for identification and quantification without an explicit attempt to de-multiplex the DIA fragment ion spectra.

Quantitative proteomics is used to determine the relative or absolute amount of proteins in a sample.207 Several quantitative proteomics methods are based on tandem mass spectrometry and it has become a preferred procedure for the structural elucidation of complex biomolecules. Rather than just providing lists of proteins identified in a certain sample, quantitative proteomics yields information about differences between samples. The methods for protein identification are identical to those used in general in qualitative proteomics but include quantification as an additional dimension. There are several quantitative proteomic approaches (iTRAQ, SILAC, SWATH, etc) both labelled and label- free, as detailed below.

An isobaric tag for relative and absolute quantitation (iTRAQ) is a reagent for tandem mass spectrometry that is used to determine the amount of proteins from different sources in a single experiment. The proteins are extracted from cells, digested and labelled with tags of the same mass.208-210 The stable isotope labelled molecules can form a covalent bond with the N-terminus and side chain amines of proteins. The iTRAQ reagents are used to label peptides from different samples that are pooled and analysed by liquid chromatography and tandem mass spectrometry.211, 212 The fragmentation of the attached tag generates a low molecular mass reporter ion that can be used to relatively quantify the peptides and the proteins from which they originated.

Stable Isotope Labelling by/with Amino acids in Cell culture (SILAC) is a technique that detects differences in protein abundance in a sample using non-radioactive isotopic labelling. The principle of SILAC is based on labelling cells by growing them in medium with either normal arginine (Arg-0, blue color) or heavy arginine (Arg-6, red color). The incorporation of the amino acids into the proteins results in a mass change of the corresponding peptides, that can be detected by a mass spectrometer.

Label-free quantification using liquid chromatography and electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS) is widely used in quantitative proteomics. However, data-dependent acquisition has low reproducibility and is biased towards abundant peptides.

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SWATH is a data-independent acquisition strategy which combined with MS/MS acquisition, allows for every detectable analyte in the sample to be fragmented, producing a complete MS and MS/MS picture without the need for re-analysis.

Figure 14. SWATH MS- Data Independent Acquisition method

Explanation: SWATH uses a wider isolation window to collect full MS/MS spectra on any detectable analyte, ensuring a full picture of every detectable peak in the sample, as shown above. https://sciex.com/technology/swath-acquisition

In data-dependent acquisition (DDA), an MS spectrum is collected on an ample m/z range. The analyte peaks are detected, sorted by descending intensity and MS/MS acquisition is triggered for the analytes in descending order, and repeated over several cycles. The major limitation of DDA is potential data gaps due to a situation where many analytes elute simultaneously and vary in abundance, the lower level analytes risk not being detected in

56 the original MS spectrum or not having enough time to capture MS/MS spectra for everything detected in MS mode.

In SWATH, an initial detection of an MS peak is not required in order to proceed to MS/MS analysis. A wider isolation window is used across the entire m/z mass detection range, collecting full MS/MS spectra on every detectable analyte in the sample (Figure 14).

Moreover, a typical MRM (multiple reaction monitoring)-based assay, requires upfront optimization of the method and selection of the compounds or MRM transitions for detection. With SWATH, a single generic MS acquisition method is used, which means that the compounds of interest are selected after the MS and MS/MS data on the sample is available, which allows re-interrogation of the data at any should, should the need arise, rather than having to re-analyse the sample (Figure 15).

Figure 15. Schematic representation of the difference between MRM and SWATH analysis.

Explanation: A MRM-based assay requires upfront optimisation of the method and pre-selection of desired compounds, whereas SWATH uses a generic MS acquisition method, allowing for selection of the compounds of interest after data is generated. This allows for data to be re-interrogated at any time, without the need to re-analyse the sample. https://sciex.com/technology/swath-acquisition

SWATH was the preferred method selected for this work due to its global quantification potential of more peptides/ proteins compared to standard label-free quantification, whilst at the same time being more economic and faster compared to available labelling approaches.

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1.5 Hypothesis

FLT3 has a major prognostic importance in AML, but inhibitor molecules that directly target FLT3 have been disappointing in the therapeutic setting. This suggests that the cells ultimately escape the effects of inhibition, identifying a need for additional targets to overcome drug resistance. This study hypothesises that different protein expression will be detected between wtFLT3 and FLT3/ITD cells during stimulation or inhibition of FLT3 pathways, and that a proteomic study of these pathways may identify proteins or pathways important to the pathogenesis of FLT3/ITD AML, which can be exploited in treatment.

1.6 Aims

The aim was to identify and biologically evaluate cell models of wtFLT3 or FLT3/ITD to then use these models in proteomic assessment. The aims were therefore in two parts:

The initial part of the thesis aimed to establish the suitability of the cell lines for evaluation of FLT3 pathways based on their biological responses to FL and FLT3 inhibitors during conditions of FLT3 activation and/or inhibition.

The second part of the thesis employed proteomic (SWATH) analysis of the cells in the conditions optimised in part 1, aiming to detect and analyse differences in protein expression that could suggest new targets for therapy in FLT3/ITD AML.

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2 MATERIALS AND METHODS

2.1 Materials

2.1.1 Reagents and buffers

The following buffers were prepared as aqueous solutions in deionised water (dH2O) (ELGA Process Water, Marlow, UK) or MilliQ water (Triple Red Ltd, Long Crendon, UK) unless otherwise specified. Reagents/buffers were purchased from Sigma-Aldrich Company Ltd, Poole, UK and solvents were purchased from the University of Manchester stores, unless otherwise specified.

2.1.1.1 Reagents for cell manipulation

Phosphate buffered saline (PBS)

1 PBS tablet dissolved in 200 ml of dH2O: 0.01M phosphate buffer, 0.0027M potassium chloride and 0.137M sodium chloride, pH 7.4

RIPA lysis buffer

50mM Tris, 150mM sodium chloride, 1% (v/v) Triton-X-100, 0.25% (w/v) sodium deoxycholate, 1mM Ethylenediaminetetraacetic acid (EDTA) pH 7.4

Mass spectrometry lysis buffer (for 1 ml)

0.5 M triethylammonium bicarbonate (TEAB) (0.5 ml), 0.05% (w/v) SDS (5µl of 10% (w/v) solution ), 6.4mM Sodium pyrophosphate (64 µl of 100 mM stock), 1

mM sodium orthovanadate (1 µl of 1 M stock), H2O (430 µl)

Dulbecco PBS (DPBS) sterile-filtered 500 ml

2.1.1.2 Media for general culture

Heat inactivated Foetal Bovine Serum from Gibco®– (Thermo Fisher Scientific, Altrincham, UK)

Roswell Park Memorial Institute 1640 (RPMI) with GlutaMAX® medium (Thermo Fisher Scientific, Altrincham, UK) with 10% (v/v) Foetal bovine serum (FBS), 1% (v/v) penicillin streptomycin and 1% (v/v) L-glutamine.

Iscove's Modified Dulbecco's Medium (IMDM) (Thermo Fisher Scientific, Altrincham, UK) with 20% (v/v) FBS, 1% (v/v) penicillin streptomycin and 1% (v/v) L-glutamine 59

2.1.1.3 Reagents for analytical techniques

SDS PAGE

Laemmli buffer x 2

62.5mM Tris-HCl, 25% (v/v) glycerol, 2% (w/v) Sodium Dodecyl Sulphate (SDS), 0.01% (w/v) bromophenol blue, 5% (v/v) β-mercaptoethanol pH 6.8

SDS-PAGE Resolving Gel (10% acrylamide) for 4 gels

MilliQ 16ml, 1.5M Tris (pH 8.8) 10 ml, 30% (w/v) Acrylamide 13.2 ml. 10% (w/v) SDS 400 µl, 10% (w/v) Ammonium persulphate 200 µl, Temed 13.2 µl

SDS-PAGE Stacking Gel (4% acrylamide) for 4 gels

MilliQ 12.3 ml, 0.5M Tris (pH 6.8) 5 ml, 30% (w/v) Acrylamide 2.7 ml, 10% (w/v) SDS 200 µl, 10% (w/v) Ammonium persulphate 100 µl, Temed 20 µl.

Running buffer

24mM Tris-HCl, 191mM glycine, 0.1% (w/v) SDS

Gel fixing buffer

50% (v/v) 100% methanol, 12% (v/v) acetic acid, 38% (v/v) milliQ water

Coomassie blue stain

0.2% (w/v) Coomassie Blue (Brilliant blue G Sigma B1131), 50% (v/v) methanol, 10% (v/v) acetic acid, 40% (v/v) milliQ water

Gel de-staining buffer

50% (v/v) methanol, 10% (v/v) acetic acid, 40% (v/v) milliQ water

WESTERN BLOT

Transfer buffer

24mM Tris-HCl, 191mM glycine, 20% (v/v) methanol

Wash buffer

PBS or TBS, 0.1% (v/v) Tween-20

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Blocking buffer for immunohybridisation

PBS with 5% (w/v) BSA

Antibody dilution buffer

PBS or TBS, 0.1% (v/v) Tween-20, 5% (w/v) Bovine Serum Albumin (BSA)

BSA Lot #SLBM7676V, A9647-100G (Sigma-Aldrich, Dorset, UK)

Antibodies

FLT3 (8F2) Rabbit mAb, #3462, Lot 11(Cell Signaling Technology, Beverly, US)

Phospho-FLT3 (Tyr589/591) (30D4) Rabbit mAb, #3464, Lot 5 (Cell Signaling Technology, Beverly, US)

ERK p44/42 MAPK (Erk1/2) Antibody #9102, Lot 4 (Cell Signaling Technology, Beverly, US)

Phospho-ERK-p44/42 MAPK (Erk1/2) (Thr202/Tyr204) Antibody #9101, Lot 12 (Cell Signaling Technology, Beverly, US)

Akt Antibody (C6727) Rabbit mAb #9272, Lot 8 (Cell Signaling Technology, Beverly, US)

Phospho-AKT (Ser 473) Rabbit mAb #4058, lot 5 (Cell Signaling Technology, Beverly, US)

MICROSCOPY

Stains

Giemsa stain Catalog No. GS500 (Sigma-Aldrich, Dorset, UK)

Prolong Gold™ anti-fade reagent with DAPI (Thermo Fisher Scientific, Altrincham, UK)

Antibodies

Phospho-FLT3 (Tyr589/591) (30D4) Rabbit mAb, #3464, Lot 5 (Cell Signaling Technology, Beverly, US) 61

FLOW CYTOMETRY

Stains

Propidium Iodide (PI) Staining Solution, 50µl/ml, Cat 51-66211E, Lot 83426 (BD Biosciences, Oxford, UK)

2.1.2 Cell lines

Two immortalised AML suspension cell lines were employed in this project, both purchased from DSMZ laboratories (Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH), Braunschweig, Germany.

The OCI AML3 cell line with wt FLT3 expression was used in parallel with the MV4-11 cell line with expression of the FLT3/ITD mutation, for all experiments.

2.1.3 Drugs

2.1.3.1 FLT3 inhibitors

Quizartinib, Free Base, product# Q-4747, Lot# QZR-101 (LC Laboratories, Massachusetts, US)

Lestaurtinib, product# L-6307, Lot# BLS-103 (LC Laboratories, Massachusetts, US)

Sunitinib, Malate Salt, product# S-8803, Lot# BST-107, (LC Laboratories, Massachusetts, US)

2.1.3.2 FLT3 ligand

Recombinant Human FLigand, catalog# 300-19, Lot# 031345 (PeproTech, London, UK)

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2.2 Methods

2.2.1 Cell culture techniques

2.2.1.1 General cell culture

The OCI-AML3 cell line was cultured in RPMI with 10% (v/v) FCS, 1% (v/v) Penicillin- Streptomycin and 1% (v/v) L-glutamine. Standard culture employed cell concentration of 0.5-2.0 x 106 cells/ml.

The MV4-11 cell line was initially cultured in a 12-well plate as advised by the manufacturer. As recommended, the cells were cultured for the first 3-5 days in IMDM with 20% (v/v) FCS, 1% (v/v) Penicillin-Streptomycin, 1% (v/v) L-glutamine and then transferred to a 25cm2 culture flask in standard media as described above. Standard culture employed cell concentration between 0.2-1.0 x 106 cells/ml.

Before use, the corresponding complete medium was warmed to 37 C in a warming bath.

Both cell lines were incubated in a Heraeus incubator (DJB Labcare Ltd,⁰ Buckinghamshire, UK) at 37°C, 5% CO2 and saturated with distilled H2O.

2.2.1.2 Cell count and viability assessment

Cell counting was performed manually using a Neubauer haemocytometer.

Both cell lines were sub-cultured three times a week, by diluting them to the required concentration/ml as assessed following the counting step.

Cell viability was assessed using flow cytometry (Section 1.2.2.5), as it provides a rapid and reliable method to quantify viable cells in a suspension.

2.2.1.3 Cell pellet preparation

To allow cell samples to be placed in long-term storage these have to be prepared into a dry cell pellet. The desired concentration of cell suspension (for example 1x107 cells) is centrifuged at 1400 RPM for 10 minutes. The supernatant is removed and the pellet is resuspended in 1 ml of cold sterile PBS and transferred to an Eppendorf tube. The Eppendorf tube is placed in a microfuge and spun at 13200 RPM for 30 seconds. The supernatant is removed and the process is repeated a second time. Following removal of the supernatant from the cell pellet, the tube with the dry cell pellet is stored in the freezer at – 80ºC.

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2.2.1.4 Protein concentration assays - BSA curve

To obtain a standard BSA curve, a stock of BSA (Sigma A2153) was made by dissolving

25 mg BSA in 1 ml dH2O. This was subsequently diluted 1:100 prior to use, to obtain a final concentration of 0.25mg/ml. The following dilutions were prepared (Table 10) and added to the corresponding wells as described below (Table 11).

Solution A B C D E F G H (µl)

BSA 0 10 20 30 40 50 60 70

dH2O 400 390 380 370 360 350 340 330

BSA 0 0.5 1 1.5 2 2.5 3 3.5 conc/well

Table 10. BSA dilutions for protein concentration assay. BSA curve determination

Explanation: A standard BSA curve was obtained by preparing a stock of BSA (by dissolving 25 mg BSA in

1 ml dH2O) and subsequently diluted 1:100 prior to use, to obtain a final concentration of 0.25mg/ml. The following dilutions were prepared as shown above and 20 µl of BioRad reagent were added to each well. A 96-well plate was used for the protein assay and an 80 µl volume of the BSA dilutions was pipetted into three wells: A123, B124, C123,etc.

Subsequently, 20 µl of BioRad reagent were added (BioRad Protein Assay Dye Reagent Concentrate 500-0006) to each well. A 96-well plate was used for the protein assay and an 80 µl volume of the BSA dilutions was pipetted into three wells: A123, B124, C123, etc.

2.2.1.5 Sample preparation

For the sample preparation, the initial dilution used was a 1:10 dilution of the protein sample to be analysed. A 5 µl volume of the solution was pipetted into the wells and completed with 75µl of dH2O, for a total volume of 100 µl/well. Subsequently, a 1:20 dilution of the protein solution was prepared and 80 µl were added to the next wells as illustrated in Table 11. Further dilutions are required to ensure the colour obtained lies between the minimum and maximum spectra of the BSA colour scheme. Both the BSA dilutions and the protein solutions were plated in triplicate in this assay, to reduce pipetting errors by enabling the calculation of the median of the three. The resulting samples were analysed using a microplate reader (Pasteur Diagnostics LP400) and the results were measured at 620nm.

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Table 11. Illustration of a 12-well plate and schematic representation of a protein assay

1 2 3 4 5 6 7 8 9 10 11 12

A BSA BSA BSA Sample Sample Sample Sample Sample Sample 0 0 0 1:10 1:10 1:10 1:20 1:20 1:20

B BSA BSA BSA Sample Sample Sample Sample Sample Sample 0.5 0.5 0.5 1:10 1:10 1:10 1:20 1:20 1:20

C BSA BSA BSA Sample Sample Sample Sample Sample Sample 1 1 1 1:10 1:10 1:10 1:20 1:20 1:20

D BSA BSA BSA Sample Sample Sample Sample Sample Sample 1.5 1.5 1.5 1:10 1:10 1:10 1:20 1:20 1:20

E BSA BSA BSA Sample Sample Sample Sample Sample Sample 2 2 2 1:10 1:10 1:10 1:20 1:20 1:20

F BSA BSA BSA Sample Sample Sample Sample Sample Sample 2.5 2.5 2.5 1:10 1:10 1:10 1:20 1:20 1:20

G BSA BSA BSA Sample Sample Sample Sample Sample Sample 3 3 3 1:10 1:10 1:10 1:20 1:20 1:20

H BSA BSA BSA Sample Sample Sample Sample Sample Sample 3.5 3.5 3.5 1:10 1:10 1:10 1:20 1:20 1:20

Explanation: For the sample preparation, a 12-well plate was employed. The initial dilution used was a 1:10 dilution of the protein sample to be analysed. A 5 µl volume of the solution was pipetted into the wells and completed with 75µl of dH2O, for a total volume of 100 µl/well. Subsequently, a 1:20 dilution of the protein solution was prepared and 80 µl were added to the next wells. Both the BSA dilutions and the protein solutions were plated in triplicate, to reduce pipetting errors by enabling the calculation of the median of the three. The resulting samples were analysed using a microplate reader (Pasteur Diagnostics LP400) and the results were measured at 620nm.

2.2.2 Analytical techniques

2.2.2.1 One-dimensional SDS-PAGE

One-dimensional SDS-PAGE gels were prepared using the Mini Protean 3 kit (Bio-Rad Laboratories Ltd, Hemel Hempstead, UK) equipment. 1.5 mm spacer plates were used.

Gel preparation

A resolving gel was prepared as described in 2.1 Reagents and buffers at 10% acrylamide concentration. The gel plates were assembled as per manufacturing protocol and the 65 resolving gel was poured up to 2 cm below the small plate top edge. The resolving gel surface was covered with MilliQ water and allowed to set for 1 hour. Subsequently, the water was poured off and the stacking gel solution was prepared at 4% (w/v) acrylamide concentration as described in 2.1 Reagents and buffers and poured up to the top edge of the plate, adding a well comb of 20 or 50 µl well volumes. It was allowed to set for 30 min. The comb was removed and the gel was assembled into the tank covering the wells with running buffer prepared as described in 2.1 Reagents and buffers.

Sample preparation and loading

Protein extraction was performed on ice, by adding 100 µl RIPA buffer to each pellet of 1x107 cells, followed by intermittent vortex for 15 min. Thereafter, the samples were centrifuged at 4°C for 10 min and the supernatant i.e. extracted protein sample, was set on ice. If the samples had been previously stored at -80°C they were allowed to defrost on ice. To load the samples, the protein (150µg) was mixed with 2x laemmli buffer with 0.01% (w/v) bromophenol blue and 5% (v/v) β-mercaptoethanol in a 1:1 equal proportion. Samples (total volume 15 µl/ well) were heated in a water bath at 98°C for 5 minutes and loaded onto the gel. A 5µl pre-stained protein standard (Bio-Rad) was loaded into the first well.

Gel running protocol

The electrophoretic separation was achieved by running the gel at 160V for approximately 1 hour, until the blue dye had reached the bottom of the gel.

Staining

Gels were stained with Coomassie blue stain (described in 2.1 Reagents and buffers). The gel was carefully released from the glass plates and covered with fixing solution (described in 2.1 Reagents and buffers) for 1 hour.

The fixing solution was then poured off and the gel was covered with Coomassie blue stain and allowed to stain for 2 to 24 hours, on a rocking platform at 4°C.

De-staining

The gel was subsequently washed repeatedly in a de-stain solution (described in 2.1 Reagents and buffers) until the background of the gel is clear. Long-term storage was done in milliQ water at 4°C in a covered container.

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2.2.2.2 Western blot analysis

For the Western blot experiments, a Mini Protean transfer kit from Biorad with tank and lid #170-3930 was used. This kit includes a blotting insert, a cooler unit which requires filling with milliQ and freezing and blotting cassettes. Other components required and used for this experiment were: a 3MM paper from Biorad mini trans; blot paper Cat no 1703932 and AmershamTM HybondTM 0.45µm PVDF membrane from GE Healthcare and Life Sciences.

After electrophoretic separation of proteins, the gel was equilibrated in transfer buffer for 5 minutes (described in 2.1 Reagents and buffers) and covered with the PVDF membrane, pre-wet in 100% methanol for 10 seconds and rinsed in milliQ for 5 minutes. The two were placed between two layers of pre-cut filter paper and subsequently between two sponges and assembled into the cassettes. The cassettes were placed in the tank which had been filled with transfer buffer (described in 2.1 Reagents and buffers). We applied a current of 250mA for 75 minutes to enable protein transfer.

Immunohybridisation

After protein transfer, the PVDF membrane was washed in PBS and then blocked in blocking buffer (described in 2.1 Reagents and buffers) for 1 hour, at room temperature on a rocking platform. Thereafter, the membrane was rinsed in PBS 3 times and incubated with the primary antibody (at the recommended antibody dilution as per the antibody data sheet) overnight at 4°C on a rocking platform. The membrane was rinsed in PBS 3 times and subsequently incubated with the Horse-radish-peroxidase (HRP)-conjugated secondary antibody (at the recommended antibody dilution as per the antibody data sheet) for 1 hour at room temperature on a rocking platform. Protein bands were then detected with an enhanced chemiluminiscence (ECL) reagent using the ChemiDoc XRS+ imaging system with Image Lab image acquisition and analysis software from BioRad.

2.2.2.3 Microscopy

Cytospin preparation

Cytospins were prepared using a Shandon Cytospin 4 from Thermo Scientific. The slides and filters were placed into the appropriate slots in the cytospin with the cardboard filters facing the centre of the cytospin. Then, 100µl sample from the cells in suspension was aliquoted to each well of the cytospin and centrifuged at 400 rpm for 10 minutes (G force

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55,45 g). The filters were then removed from the slides avoiding any contact with the cell film created and the slides were allowed to air dry for 20 minutes.

Giemsa stain

Giemsa stain is a buffered thiazine-eosinate solution designed to provide coloration of cells and used to differentiate nuclear and/or cytoplasmic morphology, using a microscope.

Giemsa staining was performed as follows. The slides were fixed in Methanol for 10 minutes and allowed to air dry for 5 minutes. Subsequently, they were introduced in

Giemsa stain (Sigma-Aldrich, Dorset, UK) at 1:20 dilution with dH2O for 10 minutes and allowed to dry for 5 minutes, followed by 2 consecutive washes in dH2O and placed on a flat surface to air dry before examination under the microscope. To visualise Giemsa stains, the Nikon 80i microscope and Hamamatsu C4742-95 camera were used on the bright light setting. Images were taken at x60 power.

DAPI stain

DAPI (4',6-diamidino-2-phenylindole) is a fluorescent stain that binds strongly to A-T rich regions in DNA. When bound to DNA, DAPI has a maximum absorption at a wavelength of 358 nm (ultraviolet) and its maximum emission is at 461 nm (blue). Therefore, for fluorescence microscopy DAPI is excited with ultraviolet light and is detected through a blue/cyan filter.

As DAPI can pass through an intact cell membrane, it can be used to stain both live and fixed cells, though it passes through the membrane less efficiently in live cells and therefore the effectiveness of the stain is lower. Cytospins were prepared as described above. Once dry, they were mounted with a cover slip and Prolong Gold™ anti-fade reagent with DAPI (Thermo Fisher Scientific, Altrincham, UK) for nuclear visualisation. They were allowed to rest for 1 hour in the dark before imaging.

2.2.2.4 Flow Cytometry

The BD FACSCanto™ II flow cytometer (BD Biosciences, Oxford, UK) was used to assess side scatter, forward scatter and fluorescence. The flow cytometric analysis was performed using BD FACSDIVATM software v7.0.1 (BD).

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Viability assessment

Cell viability can be assessed through dye exclusion methods, as live cells have intact membranes that do not allow dye penetration.

Propidium iodide (PI) is a membrane impermeant dye that is generally excluded from viable cells. It binds to double stranded DNA by intercalation between base pairs and therefore PI positive cells would suggest a late apoptotic or necrotic state, when the membrane is interrupted allowing the dye to penetrate the cell. PI is excited at 488 nm and can be used in combination with other fluorochromes excited at 488 nm such as fluorescein isothiocyanate (FITC) and phycoerythrin (PE). An adapted version of the R&D Systems Flow Cytometry Laboratory protocol for the staining of non-viable cells with PI was employed.

Cells in suspension at a concentration of 1x106 were aliquoted at 100µl in 5ml Polystyrene Round-Bottom tubes (Corning Science Mexico, ref 352054) and diluted 1:3 in IMDM or RPMI complete medium, respectively and 5μl PI was added to each tube and allowed to rest for 15 min in the dark, at RT. The resulting cell suspension was analysed counting 10,000 events per sample.

Annexin protocol

Annexin staining is used to detect and measure apoptosis. Phosphatidylserine (PS) residues are normally hidden within the plasma membrane and the appearance of these residues on the surface of the cell is an early event in apoptosis. During apoptosis, PS is translocated from the cytoplasmic face of the plasma membrane to the cell surface. Annexin V has a strong, Ca2+-dependent affinity for PS and therefore can be used as a probe for detecting apoptosis.

The one-step Annexin V staining / detection kit and reagents for use in flow cytometry were used in this project. For optimal results, the protocol provided by the manufacturer was used. An average volume of 1-5x105 cells was prepared by centrifugation and resuspended in 500 µL of 1x binding buffer. Subsequently, 5 µL of annexin V-FITC and 5 µL of propidium iodide were added and incubated at room temperature for 5 minutes in the dark. The cell suspension was thereafter analysed by flow cytometry.

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CFSE protocol

Cell Trace™ Cell proliferation kit (CFSE) was used in this project (Thermo Fisher Scientific, Abingdon, UK).

The Cell Trace ™ reagent diffuses into the cell and binds covalently to intracellular amines, resulting in a stable, fluorescent stain. The excess, unconjugated reagent diffuses to the extracellular medium where it is easily removed with complete media washes.

The vial of Cell Trace™ CFSE dye reagent was reconstituted as per manufacturer’s recommendations in 18µl of DMSO (dimethyl sulfoxide) to obtain a stock concentration of 5mM. The stock solution was prepared immediately prior to use.

Based on literature reviews and manufacturer’s recommendation regarding working CFSE concentrations, the selected concentrations for the proliferation experiments performed were 0.25 µM, 0.5 µM, 1 µM, 1.5 µM and 2 µM.

Both cell lines (OCI-AML3 and MV4-11) were tested for proliferation. Cells were prepared at a concentration of 2.5-5x105 to ensure optimal culture conditions for the cell lines employed. Once cell pellets were prepared, the cells were resuspended in pre-warmed PBS, the desired concentration of CFSE reagent was added to the sample and the cells were incubated for 20 minutes at 37ºC, in the dark. Thereafter, 5 times the original staining volume of pre-warmed complete media was added to the samples followed by incubation for 5 minutes to remove any free dye remaining in the solution. The samples were centrifuged at 1200 RPM, the supernatant was removed and the cell pellet was resuspended in pre-warmed complete media thereafter. The labelled samples were then incubated as per standard cell culture protocol at 37ºC, 5%CO2. A control sample without CFSE was prepared employing the same cell concentration and culture conditions. Flow cytometric analysis was performed at 24h, 48h and 72h to determine proliferation rate.

2.2.2.5 Mass spectrometry

Sample preparation

The experiment was set up for both study cell lines: OCI-AML3 and MV4-11. A cell suspension of 1x107 cells was used per experiment/per time point. Each cell line had 4 conditions per each time point: control sample (untreated cells), cells treated with FL, cells treated with Quizartinib and cells treated with a combination of FL and Quizartinib. The doses employed were 10nM/ml for Quizartinib and 10ng/µl for FL. The time points

70 selected for analysis were 6 hours and 24 hours. At the selected time points, dry pellets of cells (1x107) were prepared (as described in section 1.9.1.3) and stored at -80ºC awaiting analysis.

Mass spectrometry analysis

Pellets were sent on dry ice to the mass spectrometry facility at the University of Manchester, Stopford Building. At the facility, cell lysates were prepared using a freshly prepared lysis buffer (see section 1.8.1.1). A volume of 250 µl of lysis buffer was added to the frozen cell pellet and the sample was vortexed to disturb the pellet and homogenise the sample. Subsequently, the sample was sonicated in 2 pulses of 20 seconds each, followed by a rest time of 2 minutes on ice following each pulse of sonication. The probe was washed between samples with 70% (v/v) ethanol for 15 seconds followed by 70% (v/v) H2O for 15 seconds. Following sonication, the samples were spun at 13,000 RPM for 30 minutes at 4ºC and the supernatant was collected and stored at -80ºC for proteomic analysis.

A 0.1 volume of 50 mM Dithiothreitol (DTT, Fluka) was added to reduce disulphide bonds and incubated at 60°C for an hour. Samples were alkylated by 0.05 volumes of 200mM Iodoacetamide (IAA) at room temperature for 10 minutes. Proteins were digested using 10 µg trypsin (Sequencing Grade Modified Trypsin, Promega) for 100µg of protein in each sample. Trypsin was reconstituted in 1M TEAB so that final SDS concentration in the samples is less than 0.05%, trypsin added to samples and incubated at 37°C overnight.

Data independent acquisition (DIA)/SWATH-MS was performed using 100 variable precursor windows optimised for human serum. An ultra-high–performance liquid chromatography system (Eksigent ekspert nanoLC 400 autosampler and an Eksigent ekspert nanoLC 425 pump, AB SCIEX Ltd, UK) coupled to a SCIEX Triple TOF 6600 mass spectrometer with a DuoSpray Ion Source (AB SCIEX Ltd, UK) was employed. Samples were reconstituted in a buffer containing 5% (v/v) acetonitrile, 0.1% (v/v) formic acid, 100 fmol/μL of PepCalMix (MS Synthetic Peptide Calibration Kit, AB SCIEX Ltd, UK), and 10 x iRT (index retention time) standards (Biognosys AG, UK). After reconstitution, 10 μL of sample (containing 8 µg of total protein) was injected for chromatographic separation on a YMC-Triart C18 column (12nm, 150 x 0.3 mm) that was pre-coupled to a YMC-Triart C18 pre-column (12nm, 5 x 0.5 mm).

Reverse-phase chromatography was performed at 30°C with a flow rate of 5 μL/min over a 120-minute gradient. Mobile phase A contained 100% LC/MS water with 0.1% (v/v)

71 formic acid and mobile phase B contained 100% (v/v) acetonitrile with 0.1% (v/v) formic acid. Samples were run as duplicate injections with blanks between each sample. For SWATH-MS analysis samples were eluted with an analytical gradient (3 - 40% (v/v) acetonitrile, 0.1% (v/v) formic acid) and a mass spectrometry method with a total duty cycle of 2.8s comprising a TOF MS1 scan that was acquired over the mass range (m/z) 400 to 1250 followed by 100 SWATH-MS scans (m/z 100-1500) with variable m/z isolation widths, collision energy and collision energy spread. The voltage of spray was set at 5500V.

Data analysis

Data from the mass spectrometry runs was provided in an excel spreadsheet format in processed form.213 An in-depth understanding of cellular function requires knowledge of all functional interactions between the expressed proteins. The mass spectrometry data was analysed using STRING and REACTOME platforms.

• STRING is a database of known and predicted protein-protein interactions.214-215 The interactions include direct (physical) and indirect (functional) associations. These interactions stem from computational prediction, knowledge transfer between organisms and interactions aggregated from other (primary) databases. Interaction predictions in STRING are derived from 5 main sources: genomic context predictions, high-throughput lab experiments, (conserved) co-expression, automated text mining of scientific literature and previous knowledge in databases. The STRING resource is available online, at http://string-db.org/.

• REACTOME is a freely available, open-source relational database of the roles that proteins play in biological pathways and processes.216 It focuses on the reaction of the different entities (nucleic acids, proteins, vaccines, anti-cancer therapeutics and small molecules) participating in reactions, establishing a network of biological interactions that are grouped into pathways such as: metabolism, signalling, transcriptional regulation, apoptosis and disease. The REACTOME tool is available online at www.reactome.org.

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3 RESULTS AND ANALYSIS

FLT3 is recognised to be a major prognostic factor in AML. This understanding led to the creation of inhibitor molecules (tyrosine kinase inhibitors) that directly target the FLT3 molecule, in an attempt to improve the outcome of FLT3+ AML. The clinical outcomes using TKIs have been disappointing, as it was shown that AML cells ultimately escape the effects of inhibition. This suggests that utilising FLT3 inhibition solely, to change the course and/or outcome of FLT3+ AML, may never be effective and hence the need for identifying additional targets has arisen.

The ultimate goal of this experimental work was to identify alternative targets that could be used either as therapeutic targets for dual inhibition regimens or to serve as treatment monitoring tools, to aid in the assessment of the disease outcome and potentially constitute treatment alert indicators.

The initial task was therefore to replicate the observations reported in the literature, to demonstrate the role and importance of FL and TKI in the FLT3 signalling pathway and moreover, to identify potential gaps in knowledge. To further clarify this effector mechanism, it was considered essential to define the protective role of FL in AML cells after exposure to TKI and understand the changes inflicted at different levels: , proliferation and apoptosis.

Once the effect and interactions between FL-TKI-AML cell had been demonstrated and validated, samples would be produced for further in-depth study using proteomic analysis to identify and isolate potential targets for therapeutic or monitoring purposes.

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3.1 Signalling and Cell Biological Effect Analysis

Chapter aims

● Identify optimal components for the FLT3 signalling studies ● Examine the biological response of FL on the OCI-AML3 and MV4-11 cells ● Identify and select the TKI of choice for the inhibition experimental work ● Characterise the cell response to FLT3 inhibition

The overall research aim of this experimental chapter was to generate samples for proteomic analysis that would be informative for the action of FLT3 inhibitor drugs. The purpose of the chapter therefore was to select and confirm the cell lines for the study; to ensure optimal experimental conditions for cell evaluation and to generate high quality samples for proteomic analysis. The experimental work presented in this chapter therefore describes the analyses performed to confirm the validity of the selected AML cell lines as models of FLT3-dependence and FLT3-independence, it defines the optimal conditions for FLT3 inhibitor or FL use as well as the biological effects of their action to inform the subsequent proteomic studies and allow for meaningful proteomic comparisons.

3.1.1 Identification of optimal components for FLT3 signalling studies

Section aims

● Select cell lines for the experimental work ● Optimise cell culture conditions ● Identify cell number for protein concentration

3.1.1.1 Selection of cell lines for initial phase

A review of available acute myeloid leukaemia (AML) cell lines was performed (Appendix 1). Those AML cell lines with distinctive mutations (e.g. PML/RARα, BCR/ABL1, etc) were discarded since they are distinct entities with specific treatment and prognosis. The remaining cell lines were evaluated for growth characteristics in culture, or for any limitations imposed by cytokine-dependent growth (as indicated by the producer); cell lines representing rare AML entities were also not considered. Of the remaining cell lines, it was elected to include a cell line with wtFLT3 and a cell line with homozygote FLT3/ITD mutation.

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OCI-AML3 was selected to represent the wtFLT3 AML model. This particular cell line was appealing due to the added advantage of a co-existing NPM1 mutation which is common in clinical AML and which confers a good prognostic outcome. The MV4-11cell line was selected as the model for homozygote FLT3/ITD AML model. Together, these cell lines provide a basis for comparative analysis of FLT3/ITD effect.

To identify the optimal time-point for drug treatment the MV4-11 and OCI-AML3 cell lines were cultured (described in 2.2.2. General cell culture) as per the manufacturer’s recommendations. The cell viability in culture was assessed (as described in 2.2.1.2 cell count and viability assessment) using flow cytometric analysis in the presence of PI and showed 90% viability in the cell cultures at 24 hours following sub-culturing.

Therefore, the optimal time for drug experiments was chosen to be at 24 hours following sub-culturing, to ensure equal conditions for all cells.

3.1.1.2 Optimising cell culture conditions

To identify the optimal time-point for drug treatment, the MV4-11 and OCI AML3 cell lines were cultured (2.2.1.1 General cell culture) and viability was assessed (2.2.1.2 Cell count and viability assessment) using flow cytometric analysis. The principle for selection of optimal time point was to ensure best viability of cells during any treatment period, and to ensure maximal viability for the proteomic work. Based on the decision to test proteomic change at 24 hours following inhibitor-drug or FL exposure, viability testing was sequentially performed over 24-96 hours (detected as surface Annexin V). This ensured that following 24 hours to recover from splitting and re-establishment of culture, cells would have maintained viability 24 hours later (to support proteomics), and up to 72 hours later to allow drug effects to be assessed. These experiments demonstrated no significant deterioration in viability during this culture period. Although cell viability varied between experiments (80-90% for OCI-AML3 and 70-90% for MV4-11) immediately following splitting of cultures, overall viability of cultured cells was detected during the culture period (0 to 72 hours).

The initial analysis of light scatter properties demonstrated a clear separation of cells and debris, with two distinct populations within the region where intact cells lie (P1) (Figure 16). These could be gated separately to allow them to be counted (Figure 17).

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The populations were confirmed using staining with propidium iodide (Figure 18) or surface annexin V (Figure 19), to represent cells that were alive (population P2) or those that were dead or apoptotic (population P3). This demonstrated overall that cells had 70- 80% viability at 24 hours following sub-culture, compatible with expectation from cell data sheets. This time point was therefore chosen to ensure equal conditions for all cells. In later experiments describing cell death, the apoptotic fraction was also identified using annexin V staining; this yielded almost identical results.

Figure 16. Initial flow cytometry dot plots illustrating the gating technique employed for survival testing in MV4-11 cell

Explanation: For the flow cytometric analysis, 10,000 events were counted (left panel); debris and large aggregates (accounting for approximately 7% of the events were excluded as shown above, by selecting the analysis field) and the remainder of events were taken forward for further analysis (right panel).

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Figure 17. Flow cytometry dot plot and contour plot illustrating gating techniques of the MV4- 11 subpopulations (alive and dead cells)

Explanation: For the flow cytometric analysis, 10,000 events were counted and debris and large aggregates (accounting for approximately 7% of the events) were excluded and the remainder of events were taken forward for further analysis. This gating strategy allowed for separation of live (blue) and dead (green) populations. In this analysis 75% of cells fell in the blue gate (alive) and 15% in the red gate (dead).

Figure 18. Histograms illustrating cell viability in MV4-11 through differing permeability to propidium iodide (PI)

Explanation: For the flow cytometric analysis of the permeability to PI in MV4-11 cells, 10,000 events were counted and debris and large aggregates were excluded and the remainder of events were taken forward for further analysis. This analysis confirmed the identities of the two separate populations: P2 (blue) exclude PI (live cells); P3 (green) include PI (dead cells). 77

Figure 19. Histogram demonstrating surface expression of annexin V by OCI-AML3 cells confirming apoptotic cells are located with the dead cell population

Explanation: For the flow cytometric analysis of the surface expression of annexin V in OCI-AML3 cells, 10,000 events were counted and debris and large aggregates were excluded (as shown in the left panel) and the remainder of events were taken forward for further analysis (green and blue populations). This gating strategy confirmed that apoptotic cells lie with the dead cell population on the histogram P3 (green) PI (dead cells) as determined in previous experiments.

3.1.1.3 Optimising cell number for protein concentration

Correct protein concentration was important both for comparability and the planned proteomic experiments. The Bio-Rad protein assay (Bio-Rad Laboratories, Watford, UK)217 was therefore used to determine the concentration of solubilised protein. Comparison with a standard curve (e.g. BSA curve) provides a relative measurement of the protein concentration. A protein curve was created to allow evaluation of protein concentration with high reproducibility (Figure 20).

The assay demonstrated that a protein concentration of 5-10 µg (equivalent to 5x106-1x106) allowed optimal gel analysis for both cell lines. This was determined using SDS-PAGE with Coomassie staining to ensure bands were well represented and separated, together with western blot analysis to ensure appropriate detection of bands of interest. Two SDS- PAGE were performed in parallel with different protein loads, as detailed below. A cell concentration of 1x107 was lysed in 100 µl of RIPA buffer (i.e. 1x105/µl). Two 1.5 mm SDS-PAGE were prepared and a 30 µl total volume was loaded in each well. The protein concentration per well ranged from 15 to 2.5µl and the total volume of 30µl was achieved by completing with 2xLaemmli buffer.

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0.45 0.4 y = 0.0904x + 0.148

) 0.35

nM 0.3 Series1 0.25 Series2 0.2 Series3 0.15

Absorbance ( 0.1 0.05 0 0 0.5 1 1.5 2 2.5 3 3.5 Protein concentration (µg/µl)

Figure 20. Representation of protein concentration curve based on protein assay and comparison with BSA curve.

Explanation: For the determination of the optimal protein concentration to be used in future experiments, a protein concentration curve was generated, utilising samples in triplicate (series 1, 2 and 3). A protein assay is calculated through generating a standard curve of known protein concentration standards of which the BIORAD reagent wavelength absorbance is read and plotted to generate a standard curve as above. Each unknown protein sample is then calculated from the standard curve.

One gel was fixed and stained (2.2.2 Analytical Techniques) and the other was used to proceed to western blot and immunohybridization for total ERK detection. Both techniques showed that a protein load of 7.5 µl was optimal both for Coomassie stain as well as western blot analysis and was used as the basis of the studies.

Section summary

● Literature describing the characteristics of available AML cell lines was evaluated ● Two cell lines were selected as representative models: OCI-AML3 (wtFLT3) and MV4-11 (homozygote FLT3/ITD) ● Time-point for analysis was established to be at 24 hours following sub-culture, demonstrating 70-80% cell viability ● Protein load for the experimental work was determined using a protein concentration curve and validated with SDS-PAGE and western blot analysis; both techniques showed 7.5 µl to be the optimal protein load

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3.1.2 Examination of response to FL

Section aims:

● Establish expression of functional FLT3 receptor in OCI-AML3 and MV4-11 cells ● Identify potential differences in the intracellular FLT3 signalling in the 2 cell lines ● Detect any morphological response to FL stimulations in the 2 cell lines under study

3.1.2.1 Each cell line expresses a functional FLT3 receptor

It was first determined that each cell line expressed the FLT3 receptor (CD135) and so had the capability to respond to FL stimulation; i.e. it was suitable as an experimental model. Flow cytometry was used to detect expression of the FLT3 receptor at the cell surface. This demonstrated comparable and high expression by each cell line. Response to ligand binding was then assessed, and showed that following exposure to FL, each cell line down- regulated surface expression of the FLT3 receptor - a feature consistent with functional response to ligand binding and internalisation of the receptor by each cell line. Representative flow cytometry histograms showing the expression of CD135 and the change in mean fluorescence in response to FL (Figure 21).

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A B

C D

Figure 21.Representations of down-regulation of expression levels of CD135 (receptor for FL) in MV4-11 and OCI-AML3 cells before and after exposure to FL.

Explanation: Expression of CD135 was found to be present on the whole cell population for both MV-411 and OCI AML3 cells. In each case, the mean fluorescence was high with approximately a full log shift in median expression compared with control antibody. Change in mean fluorescence of CD135 by the respective cell lines is shown in panels A-D. Panel A&B show PE fluorescence by OCI-AML3. There are two peaks in the absence of ligand exposure (A) but following FL exposure the fluorescence is reduced with loss of the high expression peak and all fluorescence in the lower peak (B). A similar response is shown by MV-411 cells, but in this case there is a smaller shift between the untreated cells (C) and the FL treated cells (D).

3.1.2.2 The cell lines have different intracellular signalling related to FLT3

The signalling intermediary ERK lies downstream of FLT3 in the signalling cascade, ERK comprises two molecules of differing molecular mass but similar function (ERK1/2) and is recognised to be constitutively activated in FLT3/ITD mutated cells to form the phosphorylated ERK (pERK) molecule. In cells expressing wtFLT3, ERK is not phosphorylated at rest. Therefore, it was anticipated that the addition of FL to the wtFLT3 cell lines would cause the formation of pERK. Whether pERK would be upregulated in the FLT3/ITD cell line was unclear from the literature.

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Experimental protocols used by others suggested optimal FL stimulation was achieved with concentrations of FL between 10-100ng/ml following incubation time of 10-15 minutes. Therefore, the chosen approach was to test a range of FL concentrations on the cell lines. Using a 12-well plate assay with OCI-AML3 and MV4-11 cells at a concentration of 1x107/ml/well, the cells were exposed to serial dilutions of FL at 10ng/ml, 50ng/ml and 100ng/ml at 37°C for 15 minutes. The reaction was stopped by placing the plate on ice, followed by preparation of a dry pellet and protein lysate (Chapter 2 Materials and Methods).

As anticipated, the presence of significant pERK was observed only in the OCI-AML3 cell line following stimulation with FL. A low detection of pERK was visible in the control lanes, however this did not differ significantly from the background staining of the gel. There was no clear dose-response to ligand observed in the OCI-AML3 cells over this dose range, with a high signalling response level detected even at the lowest dose employed (Figure 22).

The blots show change to protein phosphorylation after 15 minutes exposure to drug at 37oC (cells previously cultured for 24 hours post culture-splitting). All experiments were done with equivalent cell number. Given the short experimental time it was not anticipated that expression level of the signal protein itself would be affected and that changes would be restricted to those affecting phosphorylation. Loading control lanes were performed for the relevant signal proteins but were not successful for MV4-11 (Figure 22).

pERK

Total ERK

Figure 22. OCI AML3 cell line response to stimulation with FL

Explanation: Analysis was performed with cells previously cultured for 24hr post-splitting. FL doses employed for this experiment were: 10 ng/ml, 50 ng/ml and 100 ng/ml. Exposure time to FL was 15 min. In this experiment, unstimulated MV4-11 cells act as positive control for comparison. Total ERK was used as loading control.

Legend: pERK= phosphorylated ERK 82

In contrast to OCI-AML3, the MV4-11 cell line demonstrated constitutive phosphorylation of ERK. However, a dose-dependent increase of phosphorylation still occurred, suggesting an active receptor response to FL, although with lower receptor sensitivity. Higher expression of pERK was seen at the 50-100μg of FL. To confirm the validity of this observation, a second signalling molecule (pAKT) which is also known to be activated downstream of FLT3 was tested. The pAKT demonstrated a similar pattern of response, comparable to pERK (Figure 23).

Figure 23. MV4-11 cell line post FL stimulation

Explanation: Analysis was performed with cells previously cultured for 24hr post-splitting FL doses expressed in ng/ml. FL doses tested in this experiment were: 10ng/ml, 25ng/ml, 50 ng/ml and 100 ng/ml. Exposure time to FL was 15 min. This experiment used both pERK and pAKT since the quantitative change in signalling had a lower magnitude than for MV411 cells, and it was felt that a second confirmation antibody (pAKT) would be useful to confirm the result. In this case total AKT and ERK antibodies failed. Since these results were from short term samples using the same cell numbers and identical incubation times and showed the same pattern of response on the two separate gels they were included. However, no additional loading control is available.

Legend: pAKT= phosphorylated AKT; pERK= phosphorylated ERK

The FL dose selected for the signalling experiments moving forward was the minimal ligand dose that produced full activation of pERK again comparable with concentrations used by other groups found in the literature.105-107

3.1.2.3 Detection of morphological response to FL stimulations

The signalling pathways downstream of FLT3 are recognised to affect cytoskeleton and adhesion. Therefore, it was considered that cell morphology may be altered in response to FL. Initially therefore, effects of FL on cell morphology were tested following FL stimulation of the OCI-AML3 and MV4-11 cell lines. A dose of 100ng/ml of FL was chosen for these experiments to ensure saturating receptor engagement and maximal signalling. For the initial analysis, cytospin preparations were prepared and stained using

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Giemsa stain (Chapter 2) with imaging performed at multiple time points: 1 hour, 2 hours, 4 hours and 6 hours. Illustrative images are shown for time point 4hrs.

Figure 24. The morphological features of OCI AML3 (left panel) and possible response to FL (right panel).

Explanation: Following stimulation with FL, OCI AML3 cells appear to have increased size with increased cytoplasmic basophilia which might imply further activation. The nuclear chromatin appearance is probably unchanged.

Figure 25. The morphological features of MV4-11 (left panel) and following exposure to FL (right panel).

Explanation: For the MV4-11, effects of stimulation with FL were not evident, the cell size appears unaffected and other morphological changes are not apparent.

The two cell lines differed in their intrinsic morphological features: OCI-AML3 cells are medium-size cells with basophilic and vacuolation with occasional cytoplasmic projections, the nucleus has an “open” chromatin pattern with prominent nucleoli. Following stimulation with FL, OCI-AML3 cells appear to have increased size with

84 increased cytoplasmic basophilia which might imply further activation. The nuclear chromatin appearance is probably unchanged (Figure 24). However, the effects are relatively subjective and were not considered effective proof of response that could be used as a quantitative measure without confirmation (see light scatter analysis later).

The MV4-11 cells comprise a range of medium to large-size blasts, again with basophilic cytoplasm and more obvious vacuolation, nuclei are again open in structure with prominent nucleoli. Both therefore have the appearances of primitive cells actively transcribing RNA and with features suggesting high metabolic activity (glycogen vacuoles and basophilia). For the MV4-11, effects of stimulation with FL were not evident, the cell size appears unaffected and other morphological changes are not apparent (Figure 25).

Section summary

● Each cell line expresses a functional FLT3 receptor at high level. ● Consistent with different FLT3 activation, MV4-11 demonstrate high baseline signal activation (pERK) that is not seen in OCI-AML3 ● FL induces a rapid downstream signal in OCI-AML3 cells ● FL addition induces further upregulation of pERK signalling in MV4-11 cells, but requires higher doses and responses are less marked ● There is some morphological evidence for FL responses in OCI-AML3 cells, although this is largely subjective; MV4-11 show no response

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3.1.3 Selection of TKI and cell response to FLT3 inhibition or stimulation

Section aims

● Selection of TKI of choice for the experimental work ● Define the behaviour of FLT3 receptor expression to Quizartinib and FL

3.1.3.1 TKI selection

Following literature review and preliminary results from clinical trials (Table 9), three TKIs were selected for evaluation: Lestaurtinib, Sunitinib and Quizartinib. Consistent with the previous section, pERK was selected as the marker for drug-response in these experiments. Each drug was analysed in the context of the MV4-11 cell line, which exhibits the FLT3/ITD mutation. In each case, dilutions of inhibitor drug were prepared (Figure 26), then tested against MV4-11 cells (1x107/ml) in a 24-well plate incubated for 2 hours in the incubator at 37°C, then washed twice in cold DPBS and prepared to obtain a dry pellet and protein lysate for western blot assay.

Quizartinib: Assays demonstrated inhibition of pERK signalling commencing at doses from 10nM with maximal inhibition evident at 100nM (Figure 26).

pERK

Total

Figure 26. Inhibitory response demonstrated in MV4-11 cells following treatment with Quizartinib at different doses.

Legend: pERK= phosphorylated ERK

Explanation: Quizartinib dose-response was tested in this experiment. Quizartinib doses tested for inhibitory response were: 1nM, 2 nM, 5 nM, 10 nM, 50 nM and 100 nM. Total ERK was used as loading control in this experiment.

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Lestaurtinib: Assays also demonstrated inhibition of pERK signalling at the highest doses 50 and 100nM (Figure 27).

Total ERK

pERK

Figure 27. Inhibitory response demonstrated in MV4-11 cells following treatment with Lestaurtinib at different doses.

Legend: pERK= phosphorylated ERK

Explanation: Lestaurtinib dose-response was tested in this experiment. Lestaurtinib doses tested for inhibitory response were: 1nM, 2 nM, 5 nM, 10 nM, 50 nM and 100 nM. Total ERK was used as loading control in this experiment. This WB was used for simultaneous Quizartinib and Lestaurtinib testing, hence the similarities in the images.

Sunitinib: assessment employed high drug concentrations consistent with datasheets. Similar to Lestaurtinib, inhibition was not induced until the dose range 50-100nM (Figure 28).

pERK

Total ERK

Figure 28. Inhibitory response demonstrated in MV4-11 cells following treatment with Sunitinib at different doses.

Legend: pERK= phosphorylated ERK

Explanation: Sunitinib dose-response was tested in this experiment. Sunitinib doses tested for inhibitory response were: 1nM, 2 nM, 5 nM, 10 nM, 50 nM, 100 nM, 250 nM and 500 nM. Total ERK was used as loading control in this experiment.

In each case therefore, the drugs demonstrated inhibition of pERK, confirming their effectiveness: TKIs induce inhibition of the signalling pathway downstream from FLT3. The drug selected for all future experiments was Quizartinib based on its inhibitory potency and clinical effectiveness demonstrated to date. Quizartinib had a dose response curve

87 calculated based on both the effective dose in vitro (calculated from inhibition of pERK1/2 using WB) and the selected doses also reflected the achievable drug levels achieved in serum in vivo. These data were used to select the inhibitory dose of drug employed in the experiments moving forward, as the lowest dose causing a maximal inhibitory response to pERK and were comparable with concentrations employed by other groups studying the drug.132-137

3.1.3.2 Quizartinib does not affect expression or response of CD135 to FL

It was previously shown that FL down regulates CD135 expression consistent with receptor binding and functional response. Experiments were therefore also performed in the presence of Quizartinib (Figure 29). These experiments showed that the drug alone did not significantly affect baseline receptor expression or affect the down-regulation of receptor expression that follows binding of ligand. These findings are consistent with Quizartinib affecting downstream receptor signalling rather than ligand binding and internalisation.

Figure 29. CD135 expression and response to Quizartinib in MV4-11 ( blue) and OCI-AML3 cells (red)

Legend: QL= Quizartinib and FL combination

Explanation: The presence of Quizartinib in the OCI-AML3 and MV4-11 cell lines, does not alter their baseline expression of CD135. Quizartinib does not oppose receptor downregulation in response to ligand addition to culture. The error bars represent the rSD (standard deviation adjusted for voltage). A paired T- test of data shows response to ligand in both cell lines p<0.05 in the presence or absence of quizartinib. The data for quizartinib alone were not significant although the bar charts show a consistent trend.

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Section summary

● TKIs were evaluated based on published features, three inhibitors were selected initially based on promising results in preclinical and early clinical trials. ● The inhibitors were each shown to block signalling using the downstream signal intermediary pERK ● Quizartinib was selected as the TKI of choice based on effective dose response evaluated in MV4-11 cells. ● Quizartinib does not affect the expression or response of CD135 to FL in MV4-11 cells

3.1.4 Morphological and functional cell response to FLT3 inhibition

Section aims:

● Characterise morphological effect of Quizartinib on MV4-11 and OCI-AML3 cells ● Define the changes in cell shape following exposure to Quizartinib ● Identify the effects of Quizartinib on cell proliferation and cell survival

3.1.4.1 Microscopy demonstrates effects of Quizartinib on MV4-11 but not OCI AML3 cells

Cytospins were prepared and stained using Giemsa (Chapter 2 Materials and Methods) and visualised using bright light. The effects of TKI together with untreated control cells were visualised for OCI-AML3 and MV4-11 cell lines. To ensure detectable morphological changes, a dose of 5nM was chosen for the Quizartinib, in an attempt to avoid inducing early apoptotic changes and to allow signalling-induced morphological changes to be detected prior to cell death. Imaging was performed at multiple time points: 1 hour, 2 hours, 4 hours and 6 hours. The MV4-11 change occurred in two phases: during the initial treatment at two hours there was a minor cytoskeletal response with an apparent increase in cell projections after the first hour of treatment (Figure 30).

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Figure 30. High power image showing morphological changes in MV4-11cells at 2hr post Quizartinib treatment

Explanation: The right image demonstrates marked cytoplasmic blebbing compared with control cells (left image). This may represent a cell signalling response to FLT3 inhibition in these cells, however it is also possible that this is an early feature of apoptosis, however the very early onset of these changes suggests that they may be a genuine cytoskeletal alteration in response to the inhibitor.

Subsequently, there was a progressive development of features of apoptosis affecting the MV4-11 cells with cell shrinkage, nuclear vacuole formation and chromatin condensation. Some more obvious cytoplasmic blebbing became apparent at very late time points. At the earlier times the process appeared stochastic with some cells displaying marked changes while others appeared unaffected. Allowing for variation in staining conditions and imaging, the OCI-AM3 cells showed little morphological change with the inhibitor treatment over the time course (Figure 31).

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Figure 31. The time course of morphological changes observed in OCI-AML3 and MV4-11 cells following exposure to Quizartinib

Explanation: OCI AML3 (left panel) and MV411 (right panel) taken at time 0, 1, 2, 4 and 6 hours. MV4-11 cells demonstrate progressive features of apoptosis with cell shrinkage, nuclear vacuole formation, chromatin condensation and cytoplasmic blebbing at very late time points. In contrast and allowing for variation in staining conditions and imaging, the OCI AM3 cells showed little morphological change with the inhibitor treatment over the time course.

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3.1.4.2 Flow cytometric analysis of cell shape change following Quizartinib exposure

The MV4-11 cells were analysed for FSC and SSC following drug exposure using the same gating technique as described above. The light scatter characteristics of the live population were tested to indicate possible cytoskeletal responses that could be further evaluated through other approaches. The analysis showed a change to both forward scatter and side scatter characteristics, causing a shift in the scatter plot position particularly affecting side scatter (Figure 32). These changes, occurring at 6 hours, preceded significant evidence of established apoptosis, but were consistent with the cytoskeletal changes described at earlier time points.

Figure 32. Flow cytometry contour plot of MV4-11 cells illustrating the separation of the events identified: live cells (blue) and dead cells (green).

Legend: P1=total events; P2=dead cells; P3=live cells; FSC=forward scatter; SSC=side scatter.

Explanation: For the flow cytometric analysis, 10,000 events were counted and debris and large aggregates (accounting for approximately 7% of the events) were excluded and the remainder of events were taken forward for further analysis. With this gating strategy, an evident shift was observed in the live population following exposure to Quizartinib (AC220). This is demonstrated by the reduction in the mean of both FSC and SSC between the control (untreated) cells of 145 and 67 when compared to the cells post-AC220 exposure of 127 and 49 respectively.

To assess this further, FSC and SSC were examined in more detail for the live cell population. FSC may be considered as an approximate measure of cell volume. The FSC of the treated cells was found to be reduced progressively in a time and dose-dependent manner from the 6- hour time point confirming the microscopy observations regarding the shrinking size of the cells following drug treatment (Figure 33). 92

SSC measures morphological complexity including both cytoskeleton and nucleus. The SSC analysis of the MV4-11 cells showed a time and dose-dependent reduction compared with the control sample mirroring the observations made for FSC (Figure 34). The sample treated with 2 nM drug dose revealed an interesting behaviour with a significant increase in SSC at 48 hours, greater even than the SSC of the control sample.

Figure 33. Flow cytometry analysis of FSC in MV4-11 cells following treatment with Quizartinib

Explanation: Quizartinib (AC220) was tested at different doses (1nM, 2nM, 5nM, 10nM) and at different time points (6, 24 and 48 hours). Goodness of fit: R square is 0.98 at 6hr, 1 at 24 hr and 0.99 at 48 hr. FSC of MV4-11 data shows one phase decay with significant correlation with time after 48 hours (p= 0.003)

Figure 34. Flow cytometry analysis of SSC in MV4-11 cells following treatment with Quizartinib

Explanation: Quizartinib (AC220) was tested at different doses (1nM, 2nM, 5nM, 10nM) and at different time points (6, 24 and 48 hours). Goodness of fit: R square is 0.93 at 6hr, 0.88 at 24 hr and 0.79 at 48 hr. SSC of MV411 showed significant correlation with time after 6 hrs (p=0.034) and 48 hrs (p=0.046)

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The datasets shown on the line graphs represent the combined results of 4 dose points and 3 time sets each in triplicate (a summation of 36 FACS triplicate traces). A line plot was selected therefore to summarise the data and allow the response to be easily seen. The data of mean value of 3 replicates for FSC and SSC from the scatter profile was plotted as an XY plot with a best-fit curve used to show the data trend over time. The curve fit describes the relationship of the data to the time, the best-fit curve was found to be a one phase decay curve, suggesting a logarithmic response to drug that plateaus after time. R2 shows a fit of datapoints to the one phase decay profile. Additional statistical analysis has been performed to confirm correlation of the data points with time.

3.1.4.3 Effects of Quizartinib on cell proliferation

The morphological changes observed in response to Quizartinib demonstrated clear effects on apoptosis. However, a principal clinical feature of acute myeloid leukaemia is uncontrolled proliferation, and cases of AML with FLT3/ITD are recognised to have high blast cell counts suggesting a proliferative component to FLT3 signalling effect. The effect of Quizartinib on cell proliferation was therefore tested.

MV4-11 cells were tested in cell culture at a concentration of 0.5x106/ml in 24-well plates 24 hours post sub-culturing of the cells in the presence of Quizartinib at the indicated concentrations (1nM to 10 nM range). Flow cytometric analysis was performed at 6-, 24- and 48-hours following drug treatment. To determine proliferation in the different concentrations of Quizartinib, cells were first labelled with the fluorescent dye CFSE.

There are several different approaches for analysis of cell cycle or completed cell division, each with strengths and weaknesses. The choice of the CFSE technique was based on the biological question and dye characteristics. CFSE has a relatively simple and non-toxic labelling protocol that is recommended in fragile cells and measures change to stable protein labelling of a cell. This results in a halving of mean fluorescence on each division cycle; since this measures fluorescence of a protein component, these changes do not reflect morphological change, and the stable nature of the labelled proteins allows fluorescence to be retained over many cycles of division. CFSE is therefore a frequent choice for more prolonged experiments where multiple cycles of division are measured.

Alternative measures were considered: Ki67 is a simple antibody protocol measured by FACS but represents a single point in time and hence cannot follow the number of cell cycles.

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BrDU measures incorporation into DNA and is therefore an excellent choice to measure cell cycle kinetics over a single replicative cycle, but a lengthy protocol with potential toxicity that can interfere in assessing cell division over prolonged experiments. Similarly, 7-AAD measures DNA and can be used in cell cycle kinetic measurements, however is excluded from live cells so was unsuitable for the work undertaken.

Prior to the analysis, the optimal concentration of CFSE was determined based on fluorescence intensity and toxicity; the optimal concentration was determined to be 0.25 µM. Cell fluorescence was identified in the FITC channel. Since cells were in phase for these experiments the whole population of control cells completed a cycle of division synchronously. One cycle was completed shortly after the labelling period (24 hours after splitting/feeding) and a further cycle of division was completed after 72 hours such that between 24 and 72 hours two cycles of division were completed. Since each division cycle results in a halving of fluorescence this meant a significant shift in the mean fluorescence at 72 hours (nearly one log shift). Both cell lines showed this phenomena for the control cell population, and this was not changed by the presence of FL. Quizartinib did not affect the proliferation of OCI-AML3 cells (Figure 35). In contrast, Quizartinib was shown to completely prevent the proliferation of MV4-11 cells, an effect that was not reversed by FL (Figure 36).

Control Quiz Control Quiz

FL Both FL Both

24 hours 72 hours

Figure 35. CFSE stained OCI-AML3 cells at 24 and 72 hours.

Legend: Both= Quizartinib and FL combination

Explanation: Flow cytometry demonstrates two log shifts of fluorescence in the OCI-AML3 cells, as two division cycles of division were completed for all 4 conditions tested.

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Contr Quiz Control Quiz

FL Both FL Both

24 hours 72 hours

Figure 36. CFSE stained MV4-11 cells at 24 and 72 hours.

Legend: Both= Quizartinib and FL combination

Explanation: Flow cytometry demonstrates two log shifts of fluorescence in the MV4-11 cells, as two cycles of division were completed by control cells and FL-treated cells. The cells exposed to Quizartinib (with or without FL) do not divide.

OCI-AML3 cells all showed identical behaviour in the presence of drug or ligand with a reduction in fluorescence following labelling that was equal in all conditions. In contrast, for MV411 cells, reduced fluorescence by1 log (since each division halves the cellular fluorescence this is equivalent to the 2 cycles of division that would be expected during this culture period). This reduction was not seen when Quizartinib was present consistent with the drug inducing cell cycle arrest of MV411 cells.

3.1.4.4 Effects of Quizartinib on cell survival

Similar to the cell proliferation assay, the survival or apoptosis of MV4-11 cells was tested in cell culture at a concentration of 0.5x106/ml in 24-well plates 24 hours post sub-culturing of the cells in the presence of Quizartinib at the indicated concentrations (1nM to 10 nM range). Flow cytometric analysis was performed at 6, 24- and 48-hours following drug treatment using the gating strategy previously described (Chapter 2). The results showed that at the 6-hour assessment the survival of cells did not differ from control populations. In contrast, at 24 and 48 hours there was a clear dose-dependent apoptosis with cell death increasing up to the maximum dose employed (10nM) (Figure 37).

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Figure 37. Flow cytometry analysis of survival in MV4-11 cells following treatment with Quizartinib.

Explanation: Quizartinib (AC220) was tested at different doses (1nM, 2nM, 5nM, 10nM) and at different time points (6, 24 and 48 hours). Results represent the mean values of 6 replicate values. Goodness of fit: R square is 0.71 at 6hr, 0.95 at 24 hr and 0.94 at 48 hr. Survival of MV411 showed a significant correlation with time after 24 hours: 0.14 6hrs, 0.092 24hrs 0.031 48hrs. This confirms a concentration-dependent death.

To further establish this effect and the differences between OCI-AML3 and the MV4-11 cell lines, the samples were also analysed as grouped results across the time periods, using either control, Quizartinib alone, FL alone, or a combination of the agents. Statistical analysis was also performed using a comparison of all measures at the different time points grouped according to the treatment conditions and assessed as paired samples using an ANOVA. The associated bar charts are shown for 24 hours (Figure 38) and 48 hours (Figure 39). These analyses demonstrate that Quizartinib significantly induces the death of MV4-11 but does not cause the death of OCI-AML3 cells. There is no evidence that FL protects the cells from death.

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Figure 38. Flow cytometry analysis of survival in MV4-11 and OCI AML3 cells at 24 hrs.

Explanation: The survival was tested either in control conditions or following treatment with either FL, Quizartinib, or combined agents as indicated. Bars represent the mean values with error bars expressing the SEM of 6 replicate values. Statistical analysis employed an ANOVA of matched values (GraphPad Prism; **** = p<0.001)

Figure 39. Flow cytometry analysis of survival in MV4-11 and OCI AML3 cells at 48 hrs.

Explanation: The survival was tested either in control conditions or following treatment with either FL, Quizartinib, or combined agents as indicated. Bars represent the mean values with error bars expressing the SEM of 6 replicate values. Statistical analysis employed an ANOVA of matched values (GraphPad Prism; **** = p<0.001)

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Section summary

● Quizartinib was shown to induce morphological changes and apoptosis of MV4-11 cells, but demonstrated no morphological effects on OCI-AML3 cells ● There was some indication of an early morphological change that was independent of apoptosis, but this could not reliably be confirmed. ● Flow cytometry analysis showed a reduction in both FSC and SSC measurements in MV4-11 cells following Quizartinib exposure, thus confirming the microscopy observations ● Quizartinib did not affect the proliferation, nor did it induce apoptosis in OCI-AML3 cells ● In contrast, Quizartinib completely inhibited the proliferation of MV4-11 cells and caused apoptotic cell death ● There is no evidence that FL protects the cells from Quizartinib

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3.2 Proteomic Analysis

Chapter aims

● To confirm the validity of the proteomic approach by identifying whether changes to protein expression differ between sensitive and resistant cell lines ● To test the hypothesis that signalling by FL contributes to the response of MV4-11 cells to Quizartinib ● Where differences are established, to relate these to the biological effects of the drug and to assess whether this can indicate candidate proteins for future assessment

3.2.1 Introduction

The aim of this chapter is to confirm the validity of the proteomic approach and identify whether changes to protein expression differ between sensitive (MV4-11) and resistant (OCI-AML3) cell lines, as well as test the hypothesis that signalling by FL indeed contributes to the response of MV4-11 cells to Quizartinib. The basis for these assumptions was taken from the observations made in the initial analysis and described in the section 3.1 which suggested particular themes that will be explored in this proteomic chapter.

The observations taken forward from the preceding chapter were:

1. Quizartinib was shown to have major biological effects on FLT3/ITD mutated cells in the MV4-11 cell line, but no demonstrable effect on the FLT3-wt cell line OCI-AML3. This suggests that proteomic analysis should detect differences between proteins affected by Quizartinib in the sensitive cell line MV4-11 when compared to the unresponsive cell line OCI-AML3. The first part of the analysis in this chapter therefore aims to identify potential quantitative differences in protein expression between the two cell lines when treated with Quizartinib.

2. FLT3 ligand (FL) circulates in serum, and adding FL was shown in the experiments in section 3.1 to affect signalling in MV4-11 cells (and possibly also the biological effects seen during their culture). It is recognised that FL is produced by AML cell lines and that they also express FLT3 receptor.218 It was therefore reasonable to conclude that FL was present in the cultures used in the section 3.1, and could significantly contribute to the cells’ response to Quizartinib. Based on this observation, the differences in proteomic changes triggered in the OCI-AML3 and MV4-11 cells when additional 100

exogenous FL was added to cultures (either in the presence or absence of Quizartinib) was closely analysed.

3. The data acquired in large scale proteomics is complex, so the initial analysis was used to select the conditions producing the most significant relevant changes. These were seen in the combination of FL and Quizartinib and were relatively specific for MV4- 11 cells. The proteins changed in these conditions were therefore subjected to more detailed evaluation to identify their biological function. The aim was to identify which biological processes are involved in the Quizartinib effect and which may form additional treatment targets.

4. Following this, a more detailed analysis was performed to identify and select potential candidate proteins, which might be exploited in future work.

The methods and analysis tools used for this analysis were described in (Chapter 2) and are also detailed further in the next sections. The mass spectrometry data was provided for analysis in the form of excel spreadsheets. A single analysis was performed due to time constraints and the fact that major collaborators in the proteomics department moved from the University of Manchester after the first analysis. The results of a single experiment are presented as a “proof of principle” and the analysis datasets are provided as supplementary files (Appendix 3).

3.2.2 Proteomics analysis of biologically relevant differences in protein expression between MV411 and OCI-AML3 in relation to FLT3 stimulation or inhibition

Section aims:

● Explain the initial approach to data ● Identify differences in the proteomic changes affecting the Quizartinib- sensitive MV4-11 cells compared to resistant OCI-AML3 cells when exposed to Quizartinib ● Identify potential differences in the FL effect on OCI-AML3 and MV4-11 cells ● Identify potential differences in the effect of the Quizartinib-FL combination on the OCI-AML3 and MV4-11 cells

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Initially, the number of proteins changed in the different conditions and the magnitude of changes was assessed. The aim was to indicate whether the proteomic approach was successful in detecting relevant differences, then to help select which conditions to take forward for future detailed analysis.

3.2.2.1 Initial approach to data and significance

Results were provided by Mass Spectrometry Department as a datasheet of protein expression changes by the MV4-11 or OCI-AML3 cells treated in the different conditions i.e. control samples, Quizartinib treatment alone, FL alone, or Quizartinib and FL combined.

This excel spreadsheet of the data included:

• The UniProt identification code and protein name, so each protein was identified • The quantity of the protein expressed in each condition (as determined by the SWATH mass spectrometry approach) • An assessment of the likely significance of protein expression differences compared with control samples (expressed as a p value)

The data provided from mass spectrometrists was in processed form reflecting proteins considered to be significantly upregulated or downregulated in the initial SWATH assessment.213 The proteins assigned a significance of p<0.05 became the test set. The second level of analysis was designed to further reduce the false discovery rate since proteins were then considered significant only if they were shown to form part of an interactive group by STRING (proteins not related to other changes were excluded from analysis) or within REACTOME where proteins were considered only formed a related group within a functional pathway (using the REACTOME enrichment cut off of p<0.05). The datasets with analysis of upregulated and downregulated proteins are added as Supplementary files (Appendix 3).

From this dataset, the first step of analysis was to exclude results that were not likely to be statistically significant (i.e. those with p value >0.05). Then the remaining data was used to identify those proteins whose changed expression (given as the ratio between test condition and the control sample) suggested a significant upregulated or downregulated expression that could be taken forward for further analysis. For this analysis, upregulated proteins were defined as those with more than 50% increased expression compared with

102 control; downregulated proteins were those with more than 50% decreased expression compared with control. For the group of proteins that were significantly changed, these were described as the number of proteins affected, the degree of change in expression, and their identity. The overall results are summarised below (Table 12) and described in more detail in the subsequent sections.

Table 12. Overview of the significant protein expression changes in the OCI-AML3 and MV4- 11 cell lines.

A Condition OCI AML3 MV4-11 Changed Mean change in Changed Mean change in expression relative expression vs expression relative expression vs to control (n) control (%) to control (n) control (%)

FL upregulated 43 +294 15 +322

Quiz upregulated 31 +285 98 +212

Quiz + FL upregulated 26 +294 495 +500

Condition OCI AML3 MV4-11 B Changed Mean change in Changed Mean change in expression relative expression vs expression relative expression vs to control (n) control (%) to control (n) control (%)

FL downregulated 134 -66 403 -51

Quiz downregulated 80 -62 45 -100

Quiz + FL downregulated 40 -94 454 -37

Legend: FL= FLT3 ligand; Quiz= Quizartinib

Explanation: This table summarises the changes observed in the different conditions under evaluation: section A illustrates the changes in upregulated proteins, whereas section B illustrates the changes in downregulated proteins. Results are expressed as % change (i.e. difference in expression level in test compared as a % of expression level in control. This is calculated as: (mean expression in test sample – mean expression in control sample)/expression in control sample x100%

3.2.2.2 Analysis of the difference in proteomic changes observed in MV4-11 cells compared to OCI-AML3 cells when exposed to Quizartinib

The first stage of the analysis was to study the overall number of changes to proteins expressed (upregulation or downregulation) by the two cell lines when exposed to Quizartinib. The purpose was to identify whether changes were greater for sensitive (MV4- 11) cells than insensitive (OCI-AML3) cells. Analysis of the total number of changed proteins showed little difference when only Quizartinib was present (Figure 40). Similarly,

103 analysis of the degree of change in protein expression for the affected proteins showed little difference for either upregulated or downregulated proteins (Figure 41).

Figure 40. Change in the number of proteins affected by Quizartinib for OCI-AML3 and MV4- 11 cell lines.

Explanation: The statistical evaluation was done using the Chi Squared test.

Figure 41. Level of quantitative change affecting proteins during treatment with Quizartinib for OCI-AML3 and MV4-11 cell lines.

Explanation: Error bars show SEM; the statistical evaluation was done using the Mann Whitney U test.

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The results of the section 3.1 assessing biological outcomes had shown induction of apoptosis in MV4-11 cells, but not in OCI-AML3 cells. These included the following proteins expressed during cellular apoptosis, summarised in Table 13.

Nonetheless, despite these encouraging differences, the overall changes detected were few. This was surprising given the marked biological effects observed between the conditions in the preceding experimental chapter (chapter 3.1 Signalling and Cell Biological Effect Analysis). Two possible explanations were considered for the relatively low number of differences identified.

Table 13. Isolated proteins expressed during cellular apoptosis in MV4-11 cell line

Protein name Description

TP53 regulating kinase also known as PRPK is an that in humans is encoded by the TP53RK gene. This protein is a serine/threonine protein kinase that phosphorylates p53 at Ser15. PRPK is part of the KEOPS/EKC complex, which participates in transcription control, telomere regulation and tRNA modification

Apolipoprotein E (APOE) APOE belongs to a family of fat-binding proteins (apolipoproteins) and interacts with the low-density lipoprotein receptor (LDLR), essential for the catabolism of triglyceride-rich lipoproteins. APOE is the principal cholesterol carrier in the brain and qualifies as a checkpoint inhibitor of the classical complement pathway by complex formation with activated C1q.

Annexin A1 (ANXA1) also known as lipocortin-1, is an endogenous glucocorticoid- regulated protein, which is able to counter-regulate the inflammatory events restoring homeostasis. AnxA1 and its mimetic peptides inhibit neutrophil tissue accumulation by reducing leukocyte infiltration and activating neutrophil apoptosis.

BCL2-associated X Also known as apoptosis regulator BAX, is a protein that in humans is encoded by the BAX gene. BAX is a member of the Bcl-2 gene family. BCL2 family members act as anti- or pro- apoptotic regulators that are involved in a wide variety of cellular activities.

Explanation: These proteins were identified only in the MV4-11 cell line after exposure to Quizartinib, when compared to OCI-AML3 in the same conditions.

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First, it was clear that the nature of the upregulated and downregulated proteins in the two cell lines had not been considered in this initial analysis and could suggest greater significance depending on the nature and biological function of the changed proteins. This concept is explored in the next section of the Results (3.2.3.2).

Second, it was apparent that these results were obtained after 24 hours in recently passaged culture. The preceding results had been obtained following extended cell culture and had shown changes to intrinsic signalling of the MV4-11 cells that resembled the changes seen in cells exposed to FL. It was therefore considered that FL might have significance to the action of Quizartinib in the MV4-11 cells. The analysis supporting this is described in the following two sections (3.2.2.3 & 3.2.2.4).

3.2.2.3 Analysis of the difference observed in the OCI-AML3 and MV4-11 cells after exposure to FL

When the two cell lines were exposed to FL, the experiments demonstrated that there was a different response.

Each cell line upregulated some proteins when compared with control, although the number of changed proteins was not significantly different between the lines. However, when down-regulation was assessed there was found to be a significant down-regulation of the number of changed proteins in the FLT3/ITD mutated MV4-11 cells, and this was much greater than was observed in the FLT3wt OCI-AML3 cells (Figure 42), although when the quantitative differences in the amount of upregulated or downregulated expression for the affected proteins were tested these did not differ (Figure 43).

This suggested that (consistent with the signalling response to FL seen in section 3.1) the MV4-11 cells retained a response to FL, and this affected the cells principally by down- regulating protein production. Therefore, although the major aim of the thesis was to look at proteins that underwent change in response to Quizartinib, these experiments provided evidence that the effects of Quizartinib should be assessed in the presence of FL. This is explored in the next section (3.2.2.4).

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Figure 42. Change in the number of proteins affected by FL for OCI-AML3 and MV4-11 cell lines.

Explanation: The statistical evaluation was done using the Chi Squared test.

Figure 43. Level of quantitative change affecting proteins during treatment with FL for OCI- AML3 and MV4-11 cell lines.

Explanation: Error bars represent SEM; the statistical evaluation was done using the Mann Whitney U test.

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3.2.2.4 Analysis of the differing effect observed in OCI-AML3 and MV4-11 cells when exposed to FL in combination with Quizartinib

In contrast to Quizartinib alone, when FL and Quizartinib were present together a very significant difference was seen between the MV4-11 and OCI-AML3 cells. In these conditions, there was very little demonstrable effect of Quizartinib on OCI-AML3 cells, but very significant changes observed in the MV4-11 cells, with changes affecting the number of upregulated and downregulated proteins (Figure 44), but also a significant change to the expression level of the upregulated proteins (Figure 45). These results were consistent with the major changes induced by Quizartinib occurring only when FL was present in the cell culture.

Figure 44. Level of quantitative change affecting proteins during treatment with FL for OCI- AML3 and MV4-11 cell lines.

Explanation: The statistical evaluation was done using the Mann Whitney U test.

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Both= Quiz + FL

Figure 45. Level of quantitative change affecting proteins during treatment with both FL and Quizartinib for OCI-AML3 and MV4-11 cell lines.

Legend: Both= Quizartinib and FL combination. Error bars represent SEM; the statistical evaluation was done using the Mann Whitney U test. The quantitative changes varied according to the conditions used, with a relatively small change observed when both quizartinib and FL were present together, suggesting that FL may partly oppose quizartinib effect.

Section summary

● The FLT3/ITD (MV4-11) and FLT3 wt (OCI-AML3) lines differed in their response to Quizartinib, although changes were not marked when drug was present alone; however in these conditions only the MV4-11 cells changed expression of apoptosis-related proteins ● Both cell lines responded to FL by altered protein expression suggesting that these pathways remained active (consistent with effects seen in cell signalling experiments in section 3.1); FL predominantly caused downregulated protein expression in MV4-11 cells. ● The presence of FL may best resemble physiological conditions of the cells in culture and in vivo, under these conditions the MV4 -11 cells clearly showed greater changes to protein expression in the presence of Quizartinib when compared with OCI-AML3 cells

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3.2.3 Proteomic analysis of the differences in the nature of the proteins expressed by MV4-11 and OCI-AML3 cells during Quizartinib treatment

Section aims:

● Explain the initial approach to data analysis, tools utilised and significance ● Identify the functional significance of the changes identified in the MV4-11 cells or OCI-AML3 cells when exposed to Quizartinib ● Identify the functional significance of the changes identified in the MV4-11 cells or OCI-AML3 cells when exposed to FL ● Identify the functional significance of the changes identified in the MV4-11 cells or OCI-AML3 cells when exposed to the combination Quizartinib- FL

This section analyses the nature of those proteins whose expression was changed in the different conditions in the MV4-11 or OCI-AML3 cell lines. Analysis of this type of proteomic data yields many results and therefore requires the use of specific tools designed to analyse these complex datasets to identify the way in which the differently regulated proteins contributed to the observed behaviour of the cells. A number of approaches were tried.

3.2.3.1 Initial approach to data and significance

The datasets recorded in Excel spreadsheets (3.2.2.1) also contained protein identification information in the form of a UniProt accession number. The number of proteins identified and their overlapping functions, made any protein-by-protein analysis impractical. Therefore several different bioinformatic analysis tools were compared to try to make sense of the data. In each case, the full set of changed proteins was imported into the selected analysis tool with appropriate settings, the data was then analysed to look for functional relationships between the changed proteins. These functional relationships were then used as a basis for determining their relationship to the observed changes in behaviour of the cells.

Several analysis tools were tested to analyse the data from the experiments. These included STRING (https://string-db.org/) and REACTOME (https://reactome.org/).

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• STRING is a database of known and predicted protein-protein interactions.214-215 The interactions include direct (physical) and indirect (functional) associations. These interactions originate from computational prediction, knowledge transfer between organisms and interactions aggregated from other (primary) databases. Interaction predictions in STRING are derived from 5 main sources: genomic context predictions, high-throughput lab experiments, (conserved) co-expression, automated text-mining of scientific literature and previous knowledge in databases. The STRING database currently covers 9,643,763 proteins from 2,031 organisms. The STRING resource is available online, at http://string-db.org/.

• REACTOME is a freely available, open-source relational database of the roles that proteins play in biological pathways and processes.216 It uses a relational database of signalling and metabolic molecules that is manually curated and pathways are peer- reviewed. The principle is to allow visualisation of pathways that are enriched in each dataset highlighting the biological processes implicated in the changed protein expression. The findings are principally presented as a graphical map of relationships. The REACTOME tool is available online at www.reactome.org.

REACTOME was found to provide an intuitive and effective analysis of pathways that differed with the drug and ligand and therefore, in this thesis, REACTOME analysis was applied to the sets of proteins from the proteomic experiments with separate analysis for each cell line and condition. Analysis was applied to proteins that (when compared to control cells) were enriched (+50% expression) or reduced (-50% expression) in the given conditions: FL, quizartinib, or combined FL+ quizartinib, as described in the following data analysis section. Protein lists were imported into REACTOME as UNIPROT accession list using the data entry screen and selecting the options project to human. The analysis did not include additional data on quantitative expression change since proteins had already been filtered for up-regulation or down-regulation. All proteins that were up- regulated or down regulated were therefore considered separately, solely as qualitative data (present/absent). REACTOME software settings were accepted that ascribed each protein to its known functional pathways, weighting these according to the number of elements related to each pathway, to give a pathway enrichment score. All pathways highlighted in the figures presented were enriched by p<0.05 compared to their overall representation in the body. The increasing significance being indicated by the colour shade on the default REACTOME presentation (blue).

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3.2.3.2 Analysis of the functional significance of the changes identified in the MV4-11 and OCI-AML3 cells when exposed to Quizartinib

The protein groups that had altered expression were analysed according to their ascribed function in the OCI-AML3 and MV4-11 cells. In each case, the expression was compared with control cells. This first section looks at the changes seen in the presence of Quizartinib alone.

Changes were found consistently to affect only a limited number of functional protein groups. Consistent with the changes observed in cell culture, these predominantly affected cell division (DNA replication and cell cycle), DNA damage or apoptosis (programmed cell death or DNA repair), or biosynthetic processes (chromatin organisation and metabolism of RNA). These results are depicted for Quizartinib treatment.

When downregulated proteins are considered for MV4-11 cells, the significant changes predominantly involved proteins with function in cell cycle and replication. In contrast, the OCI AML3 cells show little change (Figure 46). This is partly consistent with the findings of reduced cell replication of MV4-11 cells exposed to Quizartinib that were described section 3.1. Although they emphasise also that the changes were limited in the absence of FL.

Figure 46. Representation of the processes affected by the downregulated molecules following exposure to Quizartinib.

Explanation: The figure shows the MV4-11 cells (upper panel) and OCI-AML3 cells (lower panel). The blue highlight identifies those pathways containing affected proteins.

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A similar finding was made for upregulated proteins, although in this case the changes also showed involvement of proteins related apoptosis (Figure 47). Further consideration of the significance of these changes requires consideration of their intrinsic function (e.g. pro- apoptotic or antiapoptotic nature) and is considered later.

Figure 47. Representation of the processes affected by molecules upregulated by exposure to Quizartinib.

Explanation: The figure shows the MV4-11 cells (upper panel) and OCI-AML3 cells (lower panel). The blue highlight identifies those pathways containing affected proteins.

3.2.3.3 Analysis of the functional significance of the changes identified in the MV4-11 and OCI-AML3 cells when exposed to FL

When a similar analysis was performed for cells exposed only to FL, it was shown that a range of proteins were changed and some differences between the two cells lines were noted, however no consistently affected pathways were found either for down regulated proteins (Figure 48) or for upregulated proteins (Figure 49). In particular, although some changes were found to affect the pathways of cell proliferation or cell death, these pathways were not affected in a major way.

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Figure 48. Representation of downregulated cellular functions changed by exposure to FL.

Explanation: The figure shows the MV4-11 cells (upper panel) or OCI-AML3 cells (lower panel). The blue highlight identifies those pathways containing affected proteins.

Figure 49. Representation of downregulated cellular functions changed by exposure to Quizartinib in the presence of FL.

Explanation: The figure shows the MV4-11 cells (upper panel) or OCI-AML3 cells (lower panel). The yellow highlight identifies those pathways containing affected proteins.

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3.2.3.4 Analysis of the functional significance of the changes identified in the MV4-11 and OCI-AML3 cells when exposed to the Quizartinib-FL combination

When FL and Quizartinib were combined the differences affected the same range of biological processes but now were very marked for protein downregulation (Figure 50).

Figure 50. Representation of downregulated cellular functions changed by exposure to Quizartinib in the presence of FL.

Explanation: The figure shows the MV4-11 cells (upper panel) or OCI-AML3 cells (lower panel). The blue highlight identifies those pathways containing affected proteins.

Again, very few changes were observed in the OCI AML3 cells (lower panel), but for MV4-11 cells (upper panel) the changes were marked across all of the processes considered. The changes affecting upregulated proteins were fewer, and again appeared to relate mainly to functions involved in cell death – predominantly RNA metabolism and DNA repair processes (Figure 51).

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Figure 51. Representation of upregulated cellular functions changed by exposure to Quizartinib in the presence of FL.

Explanation: The figure shows the MV4-11 cells (upper panel) or OCI-AML3 cells (lower panel). The blue highlight identifies those pathways containing affected proteins.

Section summary

● The functional processes affected by the exposure to Quizartinib were linked predominantly to processes involved in cell growth, apoptosis or replication (as suggested by the findings in section 3.1). ● The involvement of these pathways was much more marked in MV4-11 as suggested by the experimental findings. ● The importance of FL to these responses was again highlighted by this analysis

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3.2.4 Analysis of individual proteins linked to specific biological responses in order to identify candidate proteins for clinical exploitation

Section aims:

● Identify potential therapeutic targets in the analysis of proteins related to proliferation from the Reactome dataset ● Identify potential therapeutic targets in the analysis of proteins related to apoptosis from the Reactome dataset

The purpose of this analysis phase was to look in more detail at the identities and function of the proteins examined in the preceding sections. In brief, the aim was to look at the identities of the proteins changed in particular conditions, and to look in more detail at their link to biological processes. This tested the initial hypothesis that proteomics could be used to dissect the detailed biological changes caused by Quizartinib, but was also used to address the second hypothesis that molecules that form targets for additional therapy or therapeutic monitoring could be discovered using this approach.

To perform this analysis, two biological processes were tested: 1) proliferation-associated pathways and 2) cell death pathways in the presence of combined Quizartinib and FL.

3.2.4.1 Examination of proteins related to proliferation from the Reactome dataset to identify potential therapeutic targets

The Reactome analysis allows the proteins ascribed to any particular process to be identified and assessed in further detail. This protein list includes the Uniprot identification numbers allowing the data to be cross-referenced with the protein identities that were made using proteomic analysis, and correlated with their fold-change in expression. Database search allowed these proteins to be linked to their function and cellular roles. The list of all proteins showing a 2-fold or greater change is provided in the Appendices together with their function as annotated by STRING (Appendix 2). An initial analysis reveals proteins that are directly linked to proliferation processes (such as CDK1 and CDK5 and nuclear proliferation antigen PCNA) as well as proteins whose role is structural or functional in that process (such as nuclear envelope or contractile proteins, as well as checkpoint regulators). These data were analysed using STRING to allow the functional relationships of the component molecules in the dataset (Figure 52).

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Figure 52. Analysis of the functional grouping of proteins functioning in the proliferation pathway (upregulated proteins).

Explanation: Data exported from Reactome to STRING and analysed to show protein groups at high stringency. The functional groups are shown on the figure.

It is clear from this analysis, that the components identified by Reactome represent different functional parts of the cellular proliferation process. The findings are fully consistent with the reduced proliferation demonstrated in section 3.1, but Figure 52 also illustrates the difficulties in determining which individual proteins are directly linked to Quizartinib effect (and therefore could represent additional targets of therapy). It is likely that most of these changes demonstrated reflect the downstream changes that may be expected if proliferation was inhibited. Therefore, while this is biologically informative, it shows the difficulties of interpreting proteomic approaches to find new drug targets.

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3.2.4.2 Examination of proteins related to apoptosis from the Reactome dataset to identify potential therapeutic targets

The occurrence of apoptosis depends on the balance between the pro-apoptotic and anti- apoptotic proteins expressed by the cell. Therefore, it was considered that a study of proteins related to the apoptotic pathway might reveal approaches that disrupt that balance in favour of pro-apoptotic factors. Using the same approach as had been applied to the analysis of anti-proliferative effects, an analysis was performed of the major proteins that were either induced or supressed in response to Quizartinib treatment. The proteins that are down regulated are provided in Appendix 4 together with the STRING annotation of the protein’s function, these are also summarised in a STRING relationship diagram (Figure 53).

Figure 53. Analysis of the functional grouping of proteins functioning in the apoptosis pathway (downregulated proteins).

Explanation: Data exported from Reactome to STRING and analysed to show protein groups at high stringency. The functional groups are shown on the figure.

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This pathway demonstrates the complexity of looking at these types of pathways in general, noting a down-regulation of some elements of the caspase pathway, suggesting perhaps that the effects caused by FL might be providing some protection from apoptosis. This suggestion is further borne out when upregulated proteins are considered (Figure 54) where we see an upregulation of the pro-apoptotic FAS protein, but also an upregulation of the anti-apoptotic BCL2 protein.

Figure 54. Analysis of the functional grouping of proteins functioning in the proliferation pathway (upregulated proteins).

Explanation: Data exported from Reactome to STRING and analysed to show protein groups at high stringency. The functional groups are shown on the figure.

This pathway is particularly interesting since in addition to changes in BCL2, an upregulation of signal proteins of the ROCK1 pathway was also noted. This observation aligns with the recognised role this pathways plays in apoptosis and cell growth. The proteins that are upregulated, together with the STRING annotation of the protein’s function, are provided in Appendix 5. This latter analysis therefore potentially suggests that the cellular response to Quizartinib could be modified to increase its pro-apoptotic effects through the use of inhibitors of BCL2 or through manipulation of the ROCK1 pathway.

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Section summary

● The proteomic approach allows analysis of the proteins contributing to Quizartinib effect at an individual protein level ● Proteins contributing to proliferation or apoptotic pathways could be identified ● The analysis revealed many proteins that were likely to simply reflect the functional responses observed and these would not be targets of therapy ● However, analysis of apoptotic pathways showed a complex balance of pro- apoptotic and anti-apoptotic processes when Quizartinib and FL were combined, disruption of this balance could be utilised to increase drug effect ● Candidate molecules for therapeutic targeting include BCL2 and ROCK1 pathways

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4 CONCLUSIONS AND DISCUSSION

Internal tandem duplication of the FLT3 signal molecule affects 30-40% of AML cases, and is clearly associated with adverse outcome. This finding has driven the introduction of inhibitors of FLT3 signalling into clinical practice. However, despite initial anticipation, the clinical outcomes using inhibitor molecules that directly target FLT3 have been somewhat disappointing, with no significant differences observed in clinical outcome.

The approach taken in this thesis is to use sensitive (MV4-11) and resistant (OCI-AML3) cell lines as models to explore the functional and protein pathways associated with FLT3 signalling, to look for additional targets that could be exploited to improve outcome with these inhibitor drugs. At this time this approach taken remains novel.

However, the area is progressing rapidly and the characteristics of the “ideal” FLT3 inhibitor are better understood and defined. The search for a well-tolerated, potent inhibitor with a long half-life with no inhibitory activity on KIT (to prevent excessive myelosuppression) and good TKD activity (to prevent secondary resistance) is required in order to improve clinical outcomes.219,220 Gilterinib is a promising TKI fitting the above described profile, that obtained approval in R/R FLT3+AML. Further work is underway to define the optimal combination therapies221, either with standard chemotherapy, with other targeted agents, or as maintenance after induction therapy or HSCT. No other studies have used the approach used in this work, although some have attempted to characterise the effects of kinase inhibitors on the expression of defined target molecules and genes.222-226 There remains however a need for further exploration.

This study explored an approach that might be exploited in future to improve outcome, by identifying possible targets and pathways that could be used for synergistic combinations with either quizartinib or other inhibitors acting in the FLT3 pathway. There is some proof of principle for this approach such as the development of novel drug combinations and this concept has been shown to be potentially effective.227,228

A particular outcome of this study has been the possible importance of FL effect in moderating the response to FLT3 inhibitors. Identifying a potential alternate pathway for resistance to FLT3 inhibitors that could potentially be addressed by direct receptor inhibitors or by targeting pathways related to ligand induced signalling (that may differ from the intrinsic activation of the FLT3-ITD mutation), the study also validated the relevance of the models employed that could be exploited in additional studies going forward.

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4.1 Signalling and Cell Biological Effect Experiments

The initial characterisation of MV4-11 (FLT3/ITD) and OCI-AML3 (wtFLT3) described in Section 3.1 showed these cell lines to have characteristics that made them suitable for detailed study of FL and FLT3 inhibitor therapy.

Each cell line was shown to express functional FLT3 receptor (CD135) at high level on the cell surface, and to have an active signalling response when exposed to FL. This was despite the difference in their FLT3 receptor mutation status. In particular, each cell line downregulated surface CD 135 expression in response to FL (an expected receptor internalisation) and showed activation of downstream pathways (phosphorylation of ERK1/2) by immunoblot analysis. However, consistent with them having differing FLT3 activation mechanisms, the MV4-11 cells also demonstrated high baseline signal activation that was not seen in OCI-AML3 cells.

For the TKI experiments, the choice of inhibitor was evaluated based on published characteristics; initially three inhibitors were selected based on their promising results in preclinical and early clinical trials. All three TKIs were evaluated using intracellular signalling analysis and were shown to block the signalling of FLT3, using the downstream signal intermediary pERK. Ultimately, Quizartinib was selected as the TKI of choice based on its recognised clinical effectiveness in early trials and on good dose-response characteristics demonstrated in the MV4-11 cells.

Further characterisation tested the effects of Quizartinib on the two cell lines in the presence or absence of FL. The drug reduced FL signalling in both cell lines and reduced the baseline phosphorylation of ERK in MV4-11 cells. In terms of cell biological effect, Quizartinib was shown to induce morphological changes relating to apoptosis in the MV4- 11 cells, but caused no morphological effects on OCI-AML3 cells. Flow cytometric analysis showed a reduction in both FSC and SSC measurements in MV4-11 cells following Quizartinib exposure, thus confirming the initial microscopy observations. Exogenous FL caused the induction of signalling in each cell line but was not demonstrated to affect morphology, although there was some indication of an early morphological change that was independent of apoptosis in the MV4-11 cells.

Quizartinib did not affect the proliferation or induce apoptosis in OCI-AML3 cells. In contrast, it completely inhibited the proliferation of MV4-11 cells and caused their apoptotic cell death.

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In some experiments exogenous FL was added to the cultures, but showed no significant biological effects on either cell line. It was considered however, that the cell lines showed signal pathway activation after a period in culture, consistent with FLT3 receptor activation caused by FL synthesis and release by the cell lines (in line with published literature).

These experiments used repeated analyses and the results were convincing of an effect of Quizartinib that was seen only in MV4-11 cells. However, the study could have benefitted from a more detailed study of FL effects, given the findings of the subsequent proteomics section which supports an effect of FL on the action of Quizartinib. Ideally, further experiments would have been needed to characterise the Quizartinib effects in washed cells at an early stage after passage before any potential FL synthesis, and also analyse/quantify the FL synthesis by checking for the presence of FL in the culture media. However, although samples were taken to test this, time constraints and difficulties identifying suitable antibodies, meant that it was not possible to perform this test.

Overall, the in vitro work performed provided a good basis for the proteomic studies described in the next section. In particular, the studies highlighted that both apoptosis and antiproliferative effects were induced in the MV4-11 cells when treated with Quizartinib. Additionally, the finding that MV4-11 cells continued to respond to FL despite their intrinsically activated (FLT3/ITD) form of FLT3, has particular interest in the next section where the importance of FL in the Quizartinib effect is described.

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4.2 Proteomic Analysis

The choice of SWATH proteomics for this thesis was made in part because the technique was worked up by my co-supervisors and had attractive features (chapter 1 Introduction), in particular the lack of labelling requirements and the ability to store large datasets to allow future studies to add to those datasets with more samples from comparable cell lines or primary cells and to subject these to detailed analysis.

Alternative methodologies include Stable Isotope Labelling by/with Amino acids in Cell culture (SILAC) is a technique that detects differences in protein abundance in a sample using non-radioactive isotopic labelling. The principle of SILAC is based on labelling cells by growing them in medium with either normal arginine (Arg-0, blue color) or heavy arginine (Arg-6, red color). The incorporation of the amino acids into the proteins results in a mass change of the corresponding peptides, that can be detected by a mass spectrometer.230 SILAC is a high sensitivity and high throughput method, allowing for very small amounts of proteins to be detected in a sample and being able to identify and quantify thousands of proteins simultaneously. The in vivo labelling maintains the sample stability and the high precision of the technique allows for high reproducibility of results in repeat testing.231, 232 The original experimental plan had intended that both methods be used to allow comparison and cross-validation of results. However, this did not prove possible within the framework of this MD and the availability of support in mass spectrometry.

This section evaluated the use of proteomics to investigate the treatment response to Quizartinib, and thereafter to identify potential candidate proteins for future assessment as synergistic therapeutic targets.

The section initially compared quantitative changes in protein expression between the cell lines in response to FL or Quizartinib. This analysis identified significant differences in the level of protein change between the cell lines, both in terms of the number of proteins affected and (to a lesser extent) the level of change. The section confirmed the validity of the proteomic approach by demonstrating that protein expression differed between sensitive and resistant cell lines ie. FLT3/ITD (MV4-11) and wtFLT3 (OCI-AML3). The section also drew attention to the possibility that signalling through FL contributed further to the response of MV4-11 cells to Quizartinib, since although the FLT3/ITD (MV4-11) and wtFLT3 (OCI-AML3) cell lines differed in their response to Quizartinib, these changes were not marked when the drug was present alone, and only became marked in the presence of exogenous FL. 125

Both cell lines responded to FL by altered protein expression, suggesting that these pathways remained active – an observation which is consistent with effects seen in cell signalling experiments in section 3.1. The presence of FL may best resemble physiological conditions of the cells in culture in vitro and in vivo. It was noted that FL predominantly caused down-regulated protein expression in MV4-11 cells. In the presence of Quizartinib- FL, the greatest changes in protein expression were clearly noted in the MV4 -11 cells when compared with OCI-AML3 cells.

Further analysis of the functional processes observed in the two cell lines used bioinformatic tools, focussing mainly on Reactome and String. These analyses showed that when Quizartinib was present, the proteins that were changed linked predominantly to cell growth, apoptosis and replication (as suggested by the findings in section 3.1), and the involvement of these pathways was more marked in the MV4-11 cells. The combined proteomic/bioinformatic approach also allowed identification of individual proteins that contributed to the Quizartinib effect, and potential target proteins contributing to proliferation and apoptotic pathways were identified. Many of these proteins that simply reflected proteins involved in the functional responses observed (i.e. apoptosis or proliferation) were removed from further analysis as they would not be the basis of therapeutic targeting.

However, the in-depth study of the apoptotic pathways showed a complex balance of pro- apoptotic and anti-apoptotic processes in the presence of the Quizartinib-FL combination. The disruption of this balance may provide a potential tool to increase drug effect. Particular candidate molecules for therapeutic targeting include BCL2 and ROCK1 pathways.

Overall, this section emphasises that it is important to study Quizartinib and FL in combination as this is likely to be the most physiological combination and the findings around biological processes are very consistent with the cell biological responses observed. Ideally, these finding would have been replicated and validated by repeated proteomics analysis.

One aspect that would have been useful to the study would have been to use alternative sensitive or resistant cell lines. In this regard, there are relatively few cell lines that are homozygous for FLT3-ITD and the MV4-11 cell line was purchased to fill the need for a good cell model; however a second cell line, heterozygous for FLT3-ITD, namely MOLM- 13229 (details in Appendix 1) was also tested. MOLM-13 had similar behaviour to MV4-11 126 and therefore represents a potential confirmatory model, but proved difficult to culture at high viability so was not used in this study. The initial plan also included collecting samples of primary AML cells at presentation and relapse following FLT3 inhibitor use. However, due to time constraints and the relatively few clinical cases with these characteristics this was not possible.

This study would have benefitted from the use of additional replicate samples, however an important caveat to our findings is that the chosen inhibitor (Quizarinib) has not entered clinical practice to the extent it was originally anticipated. The reasoning behind this is multi-fold and includes the safety profile (prolonged myelosuppression due to cross- inhibition of KIT and cardiac effects relating to prolongation of the QT interval on ECG) as well as acquired resistance due to development of TKD mutations due to its inhibitory profile (type II inhibitor).

However, the findings in this thesis are not devalued by this fact, as Quizartinib serves solely as a model of FLT3 inhibition and the different FLT3 drugs have similar effects on cells, differing mainly in their clinical safety profile and the ability to overcome acquired resistance to their effect. It is therefore reasonable to expand the findings of this study by replicating and extending the work using new inhibitor molecules.

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5 FUTURE WORK

Once the findings of this work have been replicated and validated through repeated proteomic analysis, the next step would be to consider the effects of inhibition of BCL2 or ROCK pathways in FLT3/ITD in the two AML cell lines. The work would then be extended to consider primary human leukaemia cells from patients with or without FLT3/ITD mutation and well as those relapsing after FLT3 inhibitor treatment. As primary leukaemia cases start to be tested by whole genome sequencing, these results could be linked to the genetic data to give an even more comprehensive analysis. This next step could be an ideal starting point for further research, potentially in the form of a new MD or PhD work.

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REFERENCES

1. Swerdlow,Campo, P. The 2008 WHO classification of lymphoid neoplasms and beyond: evolving concepts and practical applications. HEMATOLOGIA (2008). 2. Shah, A., Andersson, T. M. L., Rachet, B., Björkholm, M. & Lambert, P. C. Survival and cure of acute myeloid leukaemia in England, 1971-2006: a population-based study. Br. J. Haematol. 162, 509–516 (2013). 3. Meyers, J., Yu, Y., Kaye, J. A. & Davis, K. L. Medicare fee-for-service enrollees with primary acute myeloid leukemia: An analysis of treatment patterns, survival, and healthcare resource utilization and costs. Appl. Health Econ. Health Policy 11, 275–286 (2013). 4. Sill, H., Olipitz, W., Zebisch, A., Schulz, E. & Wölfler, A. Therapy-related myeloid neoplasms : pathobiology. Br. J. Pharmacol. 162, 792–805 (2011). 5. Cancer, T. & Atlas, G. Supplementary Appendix: Genomic and Epigenomic Landscapes of Adult De Novo Acute Myeloid Leukemia The Cancer Genome Atlas Research Network. N. Engl. J. Med. 368, 2059–74 (2013). 6. Takahashi, S. Current findings for recurring mutations in acute myeloid leukemia. Journal of Hematology and Oncology 4, (2011). 7. Kihara, R. et al. Comprehensive analysis of genetic alterations and their prognostic impacts in adult acute myeloid leukemia patients. Leukemia 28, 1586– 1595 (2014). 8. Döhner, H. et al. 8. Diagnosis and management of acute myeloid leukemia in adults: recommendations from an international expert panel, on behalf of the European LeukemiaNet. Blood 115, 453–74 (2010). 9. Bennett, J. M. et al. Proposals for the Classification of the Acute Leukaemias French‐American‐British (FAB) Co‐operative Group. Br. J. Haematol. 33, 451– 458 (1976). 10. Vardiman, J. W. et al. The 2008 revision of the World Health Organization (WHO) classification of myeloid neoplasms and acute leukemia: Rationale and important changes. Blood 114, 937–951 (2009). 11. Arber, D. A. et al. The 2016 revision to the World Health Organization classi fi cation of myeloid neoplasms and acute leukemia. Blood 127, 2391–2406 (2016). 12. Kantarjian, H. et al. Results of intensive chemotherapy in 998 patients age 65 years or older with acute myeloid leukemia or high-risk myelodysplastic syndrome: Predictive prognostic models for outcome. Cancer 106, 1090–1098 (2006). 13. Estey, E. H. Acute myeloid leukemia: 2014 Update on risk-stratification and management. Am. J. Hematol. 89, 1063–1081 (2014). 14. Mroźek, K. et al. Prognostic significance of the European LeukemiaNet standardized system for reporting cytogenetic and molecular alterations in adults with acute myeloid leukemia. J. Clin. Oncol. 30, 4515–4523 (2012).

129

15. Döhner, H. et al. Diagnosis and management of AML in adults: 2017 ELN recommendations from an international expert panel. Blood 129, 424–447 (2017). 16. Kottaridis, P. D., Gale, R. E. & Linch, D. C. FLT3 mutations and leukaemia. British Journal of Haematology 122, 523–538 (2003). 17. Rosnet, O. et al. Human FLT3/FLK2 receptor tyrosine kinase is expressed at the surface of normal and malignant hematopoietic cells. Leukemia 10, 238–48 (1996). 18. Fröhling, S. et al. Prognostic significance of activating FLT3 mutations in younger adults (16 to 60 years) with acute myeloid leukemia and normal cytogenetics: A study of the AML study group Ulm. Blood 100, 4372–4380 (2002). 19. Bacher, U., Haferlach, C., Kern, W., Haferlach, T. & Schnittger, S. Prognostic relevance of FLT3-TKD mutations in AML: The combination matters an analysis of 3082 patients. Blood 111, 2527–2537 (2008). 20. Konig, H. & Levis, M. Targeting FLT3 to treat leukemia. Expert Opin. Ther. Targets 19, 37–54 (2015). 21. Döhner, K. et al. Mutant nucleophosmin (NPM1) predicts favorable prognosis in younger adults with acute myeloid leukemia and normal cytogenetics: Interaction with other gene mutations. Blood 106, 3740–3746 (2005). 22. Li, H. Y. et al. Favorable prognosis of biallelic CEBPA gene mutations in acute myeloid leukemia patients: A meta-analysis. Eur. J. Haematol. 94, 439–448 (2015). 23. Patel, J. P. et al. Prognostic Relevance of Integrated Genetic Profiling in Acute Myeloid Leukemia. N. Engl. J. Med. 366, 1079–1089 (2012). 24. Port, M. et al. Prognostic significance of FLT3 internal tandem duplication, nucleophosmin 1, and CEBPA gene mutations for acute myeloid leukemia patients with normal karyotype and younger than 60 years: A systematic review and meta-analysis. Annals of Hematology 93, 1279–1286 (2014). 25. Cagnetta, A. et al. Role of genotype-based approach in the clinical management of adult acute myeloid leukemia with normal cytogenetics. Leukemia Research 38, 649–659 (2014). 26. Gale, R. E. et al. The impact of FLT3 internal tandem duplication mutant level, number, size, and interaction with NPM1 mutations in a large cohort of young adult patients with acute myeloid leukemia. Blood 111, 2776–2784 (2008). 27. Schnittger, S. et al. Diversity of the juxtamembrane and TKD1 mutations (Exons 13-15) in the FLT3 gene with regards to mutant load, sequence, length, localization, and correlation with biological data. Genes Chromosom. Cancer 51, 910–924 (2012). 28. Chen, X. et al. Relation of clinical response and minimal residual disease and their prognostic impact on outcome in acute myeloid leukemia. J. Clin. Oncol. 33, 1258–1264 (2015).

130

29. Walter, R. B. et al. Effect of Complete Remission and Responses Less Than Complete Remission on Survival in Acute Myeloid Leukemia: A Combined Eastern Cooperative. J Clin Oncol 28, 1766–1771 (2010). 30. Hoyos, M. et al. Core binding factor acute myeloid leukemia: The impact of age, leukocyte count, molecular findings and minimal residual disease. Eur. J. Haematol. 91, 209–218 (2013). 31. Liu Yin, J. A. et al. Minimal residual disease monitoring by quantitative RT-PCR in core binding factor AML allows risk stratification and predicts relapse: Results of the United Kingdom MRC AML-15 trial. Blood 120, 2826–2835 (2012). 32. Buccisano, F. et al. Prognostic and therapeutic implications of minimal residual disease detection in acute myeloid leukemia. Blood 119, 332–341 (2012). 33. Buckley, S. A., Appelbaum, F. R. & Walter, R. B. Prognostic and therapeutic implications of minimal residual disease at the time of transplantation in acute leukemia. Bone Marrow Transplantation 48, 630–641 (2013). 34. Vidriales, M. B. et al. Minimal residual disease evaluation by flow cytometry is a complementary tool to cytogenetics for treatment decisions in acute myeloid leukaemia. Leuk. Res. 40, 1–9 (2015). 35. Longo, D. L., Döhner, H., Weisdorf, D. J. & Bloomfield, C. D. Acute Myeloid Leukemia. New Engl. J. Med. Downloaded from nejm.org Glas. Univ. Libr. 12, 1136–52 (2015). 36. Dombret, H. & Gardin, C. An update of current treatments for adult acute myeloid leukemia. Blood 127, 53–61 (2016). 37. Yanada, M., Matsuo, K., Emi, N. & Naoe, T. Efficacy of allogeneic hematopoietic stem cell transplantation depends on cytogenetic risk for acute myeloid leukemia in first disease remission: A metaanalysis. Cancer 103, 1652–1658 (2005). 38. Cornelissen, J. J. et al. Results of a HOVON/SAKK donor versus no-donor analysis of myeloablative HLA-identical sibling stem cell transplantation in first remission acute myeloid leukemia in young and middle-aged adults: Benefits for whom? Blood 109, 3658–3666 (2007). 39. Schetelig, J. et al. Hematopoietic cell transplantation in patients with intermediate and high-risk AML: results from the randomized Study Alliance Leukemia (SAL) AML 2003 trial. Leukemia 29, 1060–1068 (2015). 40. Li, D. et al. Efficacy of allogeneic hematopoietic stem cell transplantation in intermediate-risk acute myeloid leukemia adult patients in first complete remission: A meta-analysis of prospective studies. PLoS One 10, (2015). 41. Sureda, A. et al. Indications for allo- and auto-SCT for haematological diseases, solid tumours and immune disorders: Current practice in Europe, 2015. Bone Marrow Transplant. 50, 1037–1056 (2015). 42. Fernandez, H. F. et al. Anthracycline Dose Intensification in Acute Myeloid Leukemia. N. Engl. J. Med. 361, 1249–1259 (2009).

131

43. Carella, A. M. et al. Treatment of ‘poor risk’ acute myeloid leukemia with Fludarabine, Cytarabine and G-CSF (Flag regimen): A single center study. Leuk. Lymphoma 40, 295–303 (2001). 44. Herzig, R. H., Lazarus, H. M., Wolff, S. N. & Phillips, G. L. High-dose cytosine arabinoside therapy with and without anthracycline antibiotics for remission reinduction of acute nonlymphoblastic leukemia. J. Clin. Oncol. 3, 992–997 (1985). 45. Lowenberg, B. et al. On the value of intensive remission-induction chemotherapy in elderly patients of 65+ years with acute myeloid leukemia: A randomized phase III study of the European Organization for Research and Treatment of Cancer Leukemia Group. J. Clin. Oncol. 7, 1268–1274 (1989). 46. Fenaux, P. et al. Azacitidine prolongs overall survival compared with conventional care regimens in elderly patients with low bone marrow blast count acute myeloid leukemia. J. Clin. Oncol. 28, 562–569 (2010). 47. Kantarjian, H. M. et al. Multicenter, randomized, open-label, phase III trial of decitabine versus patient choice, with physician advice, of either supportive care or low-dose cytarabine for the treatment of older patients with newly diagnosed acute myeloid leukemia. J. Clin. Oncol. 30, 2670–2677 (2012). 48. Dombret, H. et al. Results of a phase 3, multicenter, randomized, open-label study of azacitidine (AZA) vs conventional care regimens (CCR) in older patients with newly diagnosed acute myeloid leukemia (AML). 19th Congr. Eur. Hematol. Assoc. Milan Italy 99, 788–789 (2014). 49. Löwenberg, B., Downing, J. R. & Burnett, A. Acute myeloid leukemia. N. Engl. J. Med. 341, 1051–1062 (1999). 50. Grunwald, M. R. & Levis, M. J. FLT3 inhibitors for acute myeloid leukemia: A review of their efficacy and mechanisms of resistance. International Journal of Hematology 97, 683–694 (2013). 51. Small, D. FLT3 mutations: biology and treatment. Hematology / the Education Program of the American Society of Hematology. American Society of Hematology. Education Program 178–184 (2006). doi:10.1182/asheducation- 2006.1.178 52. Abu-Duhier, F. M. et al. Genomic structure of human FLT3: Implications for mutational analysis [1]. British Journal of Haematology 113, 1076–1077 (2001). 53. Rosnet, O. et al. Human FLT3/FLK2 gene: cDNA cloning and expression in hematopoietic cells. Blood 82, 1110–1119 (1993). 54. Maroc, N. et al. Biochemical characterization and analysis of the transforming potential of the FLT3/FLK2 receptor tyrosine kinase. Oncogene 8, 909–918 (1993). 55. Gary Gilliland, D. & Griffin, J. D. The roles of FLT3 in hematopoiesis and leukemia. Blood 100, 1532–1542 (2002). 56. Levis, M. & Small, D. FLT3: ITDoes matter in leukemia. Leukemia 17, 1738– 1752 (2003).

132

57. Brandts, C. H. et al. Constitutive activation of Akt by Flt3 internal tandem duplications is necessary for increased survival, proliferation, and myeloid transformation. Cancer Res. 65, 9643–50 (2005). 58. Drexler, H. G. & Quentmeier, H. Use of human leukemia-lymphoma cell lines in hematological research: effects of on human leukemia cell lines. Hum Cell 9, 309–316 (1996). 59. Zheng, R. & Small, D. Mutant FLT3 signaling contributes to a block in myeloid differentiation. Leuk. Lymphoma 46, 1679–1687 (2005). 60. Birg, F. et al. Expression of the FMSlKIT-Like Gene FLT3 in Human Acute Leukemias of the Myeloid and Lymphoid Lineages. Blood J. 80, 2584–2593 (1992). 61. Schnittger, S. et al. Prognostic impact of FLT3/ITD load in NPM1 mutated acute myeloid leukemia. Leukemia 25, 1297–1304 (2011). 62. Schlenk, R. F. et al. Mutations and Treatment Outcome in Cytogenetically Normal Acute Myeloid Leukemia. N. Engl. J. Med. 358, 1909–1918 (2008). 63. Falini, B. et al. Acute myeloid leukemia with mutated nucleophosmin (NPM1): Is it a distinct entity? Blood 117, 1109–1120 (2011). 64. Lazenby, M. et al. The prognostic relevance of flt3 and npm1 mutations on older patients treated intensively or non-intensively: A study of 1312 patients in the UK NCRI AML16 trial. Leukemia 28, 1953–1959 (2014). 65. Schneider, F. et al. The FLT3ITD mRNA level has a high prognostic impact in NPM1 mutated, butnot in NPM1 unmutated, AML witha normal karyotype. Blood 119, 4383–4386 (2012). 66. Abu-Duhier, F. M. et al. Identification of novel FLT-3 Asp835 mutations in adult acute myeloid leukaemia. Br. J. Haematol. 113, 983–988 (2001). 67. Moreno, I. et al. Incidence and prognostic value of FLT3 internal tandem duplication and D835 mutations in acute myeloid leukemia. Haematologica 88, 19–24 (2003). 68. Kottaridis, P. D. et al. Studies of FLT3 mutations in paired presentation and relapse samples from patients with acute myeloid leukemia: Implications for the role of FLT3 mutations in leukemogenesis, minimal residual disease detection, and possible therapy with FLT3 inhibitors. Blood 100, 2393–2398 (2002). 69. Thiede, C. et al. Analysis of FLT3-activating mutations in 979 patients with acute myelogenous leukemia: Association with FAB subtypes and identification of subgroups with poor prognosis. Blood 99, 4326–4335 (2002). 70. Griffith, J. et al. The Structural Basis for Autoinhibition of FLT3 by the Juxtamembrane Domain. Mol. Cell 13, 169–178 (2004). 71. Stirewalt, D. L. et al. Size of FLT3 internal tandem duplication has prognostic significance in patients with acute myeloid leukemia. Blood 107, 3724–3726 (2006).

133

72. Kusec, R. et al. More on prognostic significance of FLT3/ITD size in acute myeloid leukemia (AML) [8]. Blood 108, 405–406 (2006). 73. Ponziani, V. et al. The size of duplication does not add to the prognostic significance of FLT3 internal tandem duplication in acute myeloid leukemia patients [18]. Leukemia 20, 2074–2076 (2006). 74. Falini, B., Nicoletti, I., Martelli, M. F. & Mecucci, C. Acute myeloid leukemia carrying cytoplasmic/mutated nucleophosmin (NPMc+AML): Biologic and clinical features. Blood 109, 874–885 (2007). 75. Schnittger, S. et al. Nucleophosmin gene mutations are predictors of favorable prognosis in acute myelogenous leukemia with a normal karyotype. Blood 106, 3733–3739 (2005). 76. Nazha, A. et al. Activating internal tandem duplication mutations of the fms-like tyrosine kinase-3 (FLT3/ITD) at complete response and relapse in patients with acute myeloid leukemia. Haematologica 97, 1242–1245 (2012). 77. Murphy, K. M. et al. Detection of FLT3 internal tandem duplication and D835 mutations by a multiplex polymerase chain reaction and capillary electrophoresis assay. J. Mol. Diagnostics 5, 96–102 (2003). 78. Kiyoi, H. et al. Internal tandem duplication of the FLT3 gene is a novel modality of elongation mutation which causes constitutive activation of the product. Leukemia 12, 1333–1337 (1998). 79. Grunwald, M. R. et al. Improved FLT3 Internal Tandem Duplication PCR Assay Predicts Outcome after Allogeneic Transplant for Acute Myeloid Leukemia. Biol. Blood Marrow Transplant. 20, 1989–1995 (2014). 80. Schiller, J., Praulich, I., Krings Rocha, C. & Kreuzer, K. A. Patient-specific analysis of FLT3 internal tandem duplications for the prognostication and monitoring of acute myeloid leukemia. Eur. J. Haematol. 89, 53–62 (2012). 81. Abdelhamid, E. et al. Minimal residual disease monitoring based on FLT3 internal tandem duplication in adult acute myeloid leukemia. Leuk. Res. 36, 316– 323 (2012). 82. Scholl, S. et al. Analyses of minimal residual disease based on Flt3 mutations in allogeneic peripheral blood stem cell transplantation. J. Cancer Res. Clin. Oncol. 131, 279–283 (2005). 83. Scholl, S. et al. Minimal residual disease based on patient specific FLT3/ITD and -ITT mutations in acute myeloid leukemia. Leuk. Res. 29, 849–853 (2005). 84. Kiyoi, H., Ohno, R., Ueda, R., Saito, H. & Naoe, T. Mechanism of constitutive activation of FLT3 with internal tandem duplication in the juxtamembrane domain. Oncogene 21, 2555–2563 (2002). 85. Mizuki, M. et al. Flt3 mutations from patients with acute myeloid leukemia induce transformation of 32D cells mediated by the Ras and STAT5 pathways. Blood 96, 3907–3914 (2000).

134

86. Hayakawa, F. et al. Tandem-duplicated Flt3 constitutively activates STAT5 and MAP kinase and introduces autonomous cell growth in IL-3-dependent cell lines. Oncogene 19, 624–631 (2000). 87. Kelly, L. M. et al. FLT3 internal tandem duplication mutations associated with human acute myeloid leukemias induce myeloproliferative disease in a murine bone marrow transplant model. Blood 99, 310–318 (2002). 88. Kelly, L. M. et al. PML/RAR and FLT3/ITD induce an APL-like disease in a mouse model. Proc. Natl. Acad. Sci. 99, 8283–8288 (2002). 89. Metcalf, D. Hematopoietic cytokines. Blood 111, 485–491 (2008). 90. Matthews, W., Jordan, C. T., Wiegand, G. W., Pardoll, D. & Lemischka, I. R. A receptor tyrosine kinase specific to hematopoietic stem and progenitor cell- enriched populations. Cell 65, 1143–1152 (1991). 91. O, R., S, M., O, D. & D, B. Murine Flt3, a gene encoding a novel tyrosine kinase receptor of the PDGFR/CSF1R family. Oncogene 6, 1641–1650 (1991). 92. Lyman, S. D. et al. Molecular cloning of a ligand for the flt3 flk-2 tyrosine kinase receptor: A proliferative factor for primitive hematopoietic cells. Cell 75, 1157– 1167 (1993). 93. Lyman, S. D. et al. Identification of soluble and membrane-bound isoforms of the murine flt3 ligand generated by of mRNAs. Oncogene 10, 149–157 (1995). 94. Banu, N., Deng, B., Lyman, S. D. & Avraham, H. Modulation of haematopoietic progenitor development by Flt-3 ligand. Cytokine 11, 679–688 (1999). 95. Brashem-Stein, C., Flowers, D. A. & Bernstein, I. D. Regulation of colony forming cell generation by flt-3 ligand. Br. J. Haematol. 94, 17–22 (1996). 96. Broxmeyer, H. E. et al. Flt3 ligand stimulates/costimulates the growth of myeloid stem/progenitor cells. Exp. Hematol. 23, 1121–9 (1995). 97. Gabbianelli, M. et al. Multi-level effects of flt3 ligand on human hematopoiesis: expansion of putative stem cells and proliferation of granulomonocytic progenitors/monocytic precursors. Blood 86, 1661–1670 (1995). 98. Hirayama, F., Lyman, S. D., Clark, S. C. & Ogawa, M. The flt3 ligand supports proliferation of lymphohematopoietic progenitors and early B-lymphoid progenitors. Blood 85, 1762–8 (1995). 99. Jacobsen, S. E., Veiby, O. P., Myklebust, J., Okkenhaug, C. & Lyman, S. D. Ability of flt3 ligand to stimulate the in vitro growth of primitive murine hematopoietic progenitors is potently and directly inhibited by transforming growth factor-beta and tumor necrosis factor-alpha. Blood 87, 5016–5026 (1996). 100. Namikawa, R., Muench, M. O., de Vries, J. E. & Roncarolo, M. G. The FLK2/FLT3 ligand synergizes with interleukin-7 in promoting stromal-cell- independent expansion and differentiation of human fetal pro-B cells in vitro. Blood 87, 1881–90 (1996).

135

101. Ray, R. J., Paige, C. J., Furlonger, C., Lyman, S. D. & Rottapel, R. Flt3 ligand supports the differentiation of early B cell progenitors in the presence of interleukin-11 and interleukin-7. Eur. J. Immunol. 26, 1504–1510 (1996). 102. Veiby, O. P., Lyman, S. D. & Jacobsen, S. E. W. Combined signaling through interleukin-7 receptors and flt3 but not c-kit potently and selectively promotes B- cell commitment and differentiation from uncommitted murine bone marrow progenitor cells. Blood 88, 1256–1265 (1996). 103. McKenna, H. J., de Vries, P., Brasel, K., Lyman, S. D. & Williams, D. E. Effect of flt3 ligand on the ex vivo expansion of human CD34+ hematopoietic progenitor cells. Blood 86, 3413–20 (1995). 104. Mackarehtschian, K. et al. Targeted disruption of the flk2/flt3 gene leads to deficiencies in primitive hematopoietic progenitors. Immunity 3, 147–161 (1995). 105. Mckenna, H. J. et al. Mice lacking flt3 ligand have deficient hematopoiesis affecting hematopoietic progenitor cells, dendritic cells, and natural killer cells. Bloo 95, 3489–3497 (2000). 106. Sitnicka, E. et al. Key role of flt3 ligand in regulation of the common lymphoid progenitor but not in maintenance of the hematopoietic stem cell pool. Immunity 17, 463–472 (2002). 107. von Muenchow, L. et al. Permissive roles of cytokines interleukin-7 and Flt3 ligand in mouse B-cell lineage commitment. Proc. Natl. Acad. Sci. 113, E8122– E8130 (2016). 108. Beaudin, A. E., Boyer, S. W. & Forsberg, E. C. Flk2/Flt3 promotes both myeloid and lymphoid development by expanding non-self-renewing multipotent hematopoietic progenitor cells. Exp. Hematol. 42, 218–229 (2014). 109. Dolence, J. J., Gwin, K. A., Shapiro, M. B. & Medina, K. L. Flt3 signaling regulates the proliferation, survival, and maintenance of multipotent hematopoietic progenitors that generate B cell precursors. Exp. Hematol. 42, 380– 393 (2014). 110. Balciunaite, G., Ceredig, R., Massa, S. & Rolink, A. G. A B220+CD117+CD19- hematopoietic progenitor with potent lymphoid and myeloid developmental potential. Eur. J. Immunol. 35, 2019–2030 (2005). 111. Karsunky, H., Inlay, M. A., Serwold, T., Bhattacharya, D. & Weissman, I. L. Flk2 + common lymphoid progenitors possess equivalent differentiation potential for the B and T lineages. Blood 111, 5562–5570 (2008). 112. Crisan, M. & Dzierzak, E. Correction: The many faces of hematopoietic stem cell heterogeneity. Development doi: 10.1242/dev.114231. Development 144, 4195– 4195 (2017). 113. Eaves, C. J. Hematopoietic stem cells: Concepts, definitions, and the new reality. Blood 125, 2605–2613 (2015). 114. Notta, F. et al. Distinct routes of lineage development reshape the human blood hierarchy across ontogeny. Science (80-. ). 351, (2016).

136

115. Tsapogas, P., Mooney, C. J., Brown, G. & Rolink, A. The cytokine FLigand in normal and malignant hematopoiesis. International Journal of Molecular Sciences 18, (2017). 116. Endele, M., Etzrodt, M. & Schroeder, T. Instruction of hematopoietic lineage choice by cytokine signaling. Experimental Cell Research 329, 207–213 (2014). 117. Sarrazin, S. & Sieweke, M. Integration of cytokine and transcription factor signals in hematopoietic stem cell commitment. Seminars in Immunology 23, 326–334 (2011). 118. Mooney, C. J., Cunningham, A., Tsapogas, P., Toellner, K. M. & Brown, G. Selective expression of Flt3 within the mouse hematopoietic stem cell compartment. Int. J. Mol. Sci. 18, (2017). 119. Kayser, S. et al. The impact of therapy-related acute myeloid leukemia (AML) on outcome in 2853 adult patients with newly diagnosed AML. Blood 117, 2137– 2145 (2011). 120. Shih, L. Y. et al. Internal tandem duplication of FLT3 in relapsed acute myeloid leukemia: A comparative analysis of bone marrow samples from 108 adult patients at diagnosis and relapse. Blood 100, 2387–2392 (2002). 121. Shih, L. Y. et al. Acquisition of FLT3 or N-ras mutations is frequently associated with progression of myelodysplastic syndrome to acute myeloid leukemia. Leukemia 18, 466–475 (2004). 122. Mead, A. J. et al. FLT3 tyrosine kinase domain mutations are biologically distinct from and have a significantly more favorable prognosis than FLT3 internal tandem duplications in patients with acute myeloid leukemia. Blood 110, 1262– 1270 (2007). 123. Smith, C. C. et al. Crenolanib is a selective type I pan-FLT3 inhibitor. Proc. Natl. Acad. Sci. 111, 5319–5324 (2014). 124. Smith, C. C. et al. Activity of ponatinib against clinically-relevant AC220- resistant kinase domain mutants of FLT3/ITD. Blood 121, 3165–3171 (2013). 125. Blau, O., Berenstein, R., Sindram, A. & Blau, I. W. Molecular analysis of different FLT3/ITD mutations in acute myeloid leukemia. Leuk. Lymphoma 54, 145–152 (2013). 126. Smith, C. C. & Shah, N. P. The Role of Kinase Inhibitors in the Treatment of Patients with Acute Myeloid Leukemia. Am. Soc. Clin. Oncol. Educ. B. 33, 313– 318 (2013). 127. Daver, N. et al. Secondary mutations as mediators of resistance to targeted therapy in leukemia. Blood 125, 3236–3245 (2015). 128. Ozeki, K. et al. Biologic and clinical significance of the FLT3 transcript level in acute myeloid leukemia. Blood 103, 1901–1908 (2004). 129. Pratz, K. W. et al. FLT3-mutant allelic burden and clinical status are predictive of response to FLT3 inhibitors in AML. Blood 115, 1425–1432 (2010).

137

130. Cortes, J. E. et al. A Phase II Open-Label, Ac220 Monotherapy Efficacy Study In Patients with Refractory/Relapsed FLT3/ITD Positive Acute Myeloid Leukemia: Updated Interim Results. ASH Annu. Meet. Abstr. 118, 2576 (2011). 131. Bowen, D. et al. AC220 (Quizartinib) Can Be Safely Combined With Conventional Chemotherapy In Older Patients With Newly Diagnosed Acute Myeloid Leukaemia: Experience From The AML18 Pilot Trial. Blood 122, 622 (2013). 132. Tallman, M. S. et al. Results Of a Phase 2 Randomized, Open-Label, Study Of Lower Doses Of Quizartinib (AC220; ASP2689) In Subjects With FLT3/ITD Positive Relapsed Or Refractory Acute Myeloid Leukemia (AML). Blood 122, 494 (2013). 133. Levis, M. et al. A FLT3-targeted tyrosine kinase inhibitor is cytotoxic to leukemia cells in vitro and in vivo. Blood 99, 3885–3891 (2002). 134. Knapper, S. et al. The effects of Lestaurtinib (CEP701) and PKC412 on primary AML blasts: The induction of cytotoxicity varies with dependence on FLT3 signaling in both FLT3-mutated and wild-type cases. Blood 108, 3494–3503 (2006). 135. Knapper, S. et al. A phase 2 trial of the FLT3 inhibitor Lestaurtinib (CEP701) as first-line treatment for older patients with acute myeloid leukemia not considered fit for intensive chemotherapy. Blood 108, 3262–3270 (2006). 136. O’Farrell, A. M. et al. An Innovative Phase I Clinical Study Demonstrates Inhibition of FLT3 Phosphorylation by SU11248 in Acute Myeloid Leukemia Patients. Clin. Cancer Res. 9, 5465–5476 (2003). 137. Fiedler, W. et al. A phase 1 study of SU11248 in the treatment of patients with refractory or resistant acute myeloid leukemia (AML) or not amenable to conventional therapy for the disease. Blood 105, 986–993 (2005). 138. Stone, R. M. FLT3 Inhibitors in Acute Myeloid Leukemia: An Update. Ann. Hematol. Acute Leuk. XIII Biol. Treat. Strateg. Munich Ger. Start 20110227 Conf. End 20110302.Conference Publ. 90, S70–S72 (2011). 139. Fischer, T. et al. Phase IIB trial of oral midostaurin (PKC412), the FMS-like tyrosine kinase 3 receptor (FLT3) and multi-targeted kinase inhibitor, in patients with acute myeloid leukemia and high-risk myelodysplastic syndrome with either wild-type or mutated FLT3. J. Clin. Oncol. 28, 4339–4345 (2010). 140. Smith, B. D. et al. Single Agent CEP-701, a Novel FLT-3 Inhibitor, Shows Initial Response in Patients with Refractory Acute Myeloid Leukemia. Blood 100, Abstract No. 314 (2002). 141. Zhang, W. et al. Mutant FLT3: A direct target of Sorafenib in acute myelogenous leukemia. J. Natl. Cancer Inst. 100, 184–198 (2008). 142. Crump, M. et al. A randomized phase i clinical and biologic study of two schedules of Sorafenib in patients with myelodysplastic syndrome or acute myeloid leukemia: A NCIC (National Cancer Institute of Canada) Clinical Trials Group Study. Leuk. Lymphoma 51, 252–260 (2010).

138

143. Metzelder, S. et al. Compassionate use of Sorafenib in FLT3/ITD - Positive acute myeloid leukemia: Sustained regression before and after allogeneic stem cell transplantation. Blood 113, 6567–6571 (2009). 144. Sharma, M. et al. Treatment of FLT3/ITD-positive acute myeloid leukemia relapsing after allogeneic stem cell transplantation with Sorafenib. Biol. Blood Marrow Transplant. 17, 1874–1877 (2011). 145. MetzelDer, S. K. et al. High activity of Sorafenib in FLT3/ITD-positive acute myeloid leukemia synergizes with allo-immune effects to induce sustained responses. Leukemia 26, 2353–2359 (2012). 146. Giles, F. J. et al. SU5416, a small molecule tyrosine kinase receptor inhibitor, has biologic activity in patients with refractory acute myeloid leukemia or myelodysplastic syndromes. Blood 102, 795–801 (2003). 147. Fiedler, W. et al. A phase 2 clinical study of SU5416 in patients with refractory acute myeloid leukemia. Blood 102, 2763–2767 (2003). 148. DeAngelo, D. J. et al. Phase 1 clinical results with tandutinib (MLN518), a novel FLT3 antagonist, in patients with acute myelogenous leukemia or high-risk myelodysplastic syndrome: Safety, pharmacokinetics, and pharmacodynamics. Blood 108, 3674–3681 (2006). 149. Pratz, K. W. et al. A pharmacodynamic study of the FLT3 inhibitor KW-2449 yields insight into the basis for clinical response. Blood 113, 3938–3946 (2009). 150. Martinelli, G. et al. Effect of Quizartinib (AC220) on response rates and long- term survival in elderly patients with FLT3/ITD positive or negative relapsed/refractory acute myeloid leukemia. J. Clin. Oncol. 31, 7021 (2013). 151. Randhawa JK, Kantarjian HM, Borthakur G, et al. Results of a Phase II Study of Crenolanib in Relapsed/Refractory Acute Myeloid Leukemia Patients (Pts) with Activating FLT3 Mutations [abstract]. Blood. 2014;124(21). Abstract 389. Blood 124, 389 (2014). 152. Shah, N. P. et al. Ponatinib in patients with refractory acute myeloid leukaemia: Findings from a phase 1 study. British Journal of Haematology 162, 548–552 (2013). 153. Alexander E. Perl, Jessica K. Altman, Jorge E. Cortes, Catherine C. Smith, Mark Litzow, Maria R. Baer, David F. Claxton, Harry P. Erba, Stanley C. Gill, Stuart L. Goldberg, Joseph G. Jurcic, Richard A. Larson, Charles Liu, Ellen K. Ritchie, Gary J. Schill, E. B. and M. J. L. Final Results of the Chrysalis Trial: A First-in- Human Phase 1/2 Dose-Escalation, Dose-Expansion Study of Gilteritinib (ASP2215) in Patients with Relapsed/Refractory Acute Myeloid Leukemia (R/R AML). Blood (ASH Annu. Meet. Abstr. 128, (2016). 154. Borthakur, G. et al. Report of a phase 1/2 study of a combination of azacitidine and cytarabine in acute myelogenous leukemia and high-risk myelodysplastic syndromes. Leuk. Lymphoma 51, 73–78 (2010). 155. Kornblau, S. M. et al. Simultaneous activation of multiple signal transduction pathways confers poor prognosis in acute myelogenous leukemia. Blood 108, 2358–2365 (2006).

139

156. Mohi, M. G. et al. Combination of rapamycin and protein tyrosine kinase (PTK) inhibitors for the treatment of leukemias caused by oncogenic PTKs. Proc. Natl. Acad. Sci. 101, 3130–3135 (2004). 157. Weisberg, E. et al. Potentiation of antileukemic therapies by the dual PI3K PDK-1 inhibitor, BAG956: Effects on BCR-ABL and mutant FLT3-expressing cells. Blood 111, 3723–3734 (2008). 158. Ikezoe, T. et al. The antitumor effects of sunitinib (formerly SU11248) against a variety of human hematologic malignancies: enhancement of growth inhibition via inhibition of mammalian target of rapamycin signaling. Mol. Cancer Ther. 5, 2522–2530 (2006). 159. Nishioka, C. et al. Blockade of MEK/ERK signaling enhances sunitinib-induced growth inhibition and apoptosis of leukemia cells possessing activating mutations of the FLT3 gene. Leuk. Res. 32, 865–872 (2008). 160. Al Shaer, L. et al. Heat shock protein 90 inhibition is cytotoxic to primary AML cells expressing mutant FLT3 and results in altered downstream signalling. Br. J. Haematol. 141, 483–493 (2008). 161. Nishioka, C. et al. MS-275, a novel histone deacetylase inhibitor with selectivity against HDAC1, induces degradation of FLT3 via inhibition of chaperone function of heat shock protein 90 in AML cells. Leuk. Res. 32, 1382–1392 (2008). 162. Sandmaier, B., McSweeney, C, Y. & R, S. Nonmyeloablative transplants: preclinical and clinical results. Semin. Oncol. 27, 78–81 (2000). 163. Chen, Y. Bin et al. Phase i trial of maintenance Sorafenib after allogeneic hematopoietic stem cell transplantation for fms-like tyrosine kinase 3 internal tandem duplication acute myeloid leukemia. Biol. Blood Marrow Transplant. 20, 2042–2048 (2014). 164. Antar, A., Kharfan-Dabaja, M. A., Mahfouz, R. & Bazarbachi, A. Sorafenib maintenance appears safe and improves clinical outcomes in FLT3/ITD acute myeloid leukemia after allogeneic hematopoietic cell transplantation. Clin. Lymphoma, Myeloma Leuk. 15, 298–302 (2015). 165. Nakano, Y. et al. Molecular evolution of acute myeloid leukaemia in relapse: Unstable N- ras and FLT3 genes compared with p53 gene. Br. J. Haematol. 104, 659–664 (1999). 166. Piloto, O. et al. Prolonged exposure to FLT3 inhibitors leads to resistance via activation of parallel signaling pathways. Blood 109, 1643–1652 (2007). 167. Goodsell, D. S. The molecular perspective: The ras oncogene. Stem Cells 17, 235– 236 (1999). 168. Chu, S. H. & Small, D. Mechanisms of resistance to FLT3 inhibitors. Drug Resist. Updat. 12, 8–16 (2009). 169. Tai, Y. T. et al. Role of B-cell-activating factor in adhesion and growth of human multiple myeloma cells in the bone marrow microenvironment. Cancer Res. 66, 6675–6682 (2006).

140

170. Sexauer, A. et al. Terminal myeloid differentiation in vivo is induced by FLT3 inhibition in FLT3/ITDAML. Blood 120, 4205–4214 (2012). 171. Levis, M. et al. Plasma inhibitory activity (PIA): A pharmacodynamic assay reveals insights into the basis for cytotoxic response to FLT3 inhibitors. Blood 108, 3477–3483 (2006). 172. Breitenbuecher, F. et al. A novel molecular mechanism of primary resistance to FLT3-kinase inhibitors in AML. Blood 113, 4063–4073 (2009). 173. Zhou, J. et al. Enhanced activation of STAT pathways and overexpression of survivin confer resistance to FLT3 inhibitors and could be therapeutic targets in AML. Blood 113, 4052–4062 (2009). 174. Kohl, T. M. et al. BH3 mimetic ABT-737 neutralizes resistance to FLT3 inhibitor treatment mediated by FLT3-independent expression of BCL2 in primary AML blasts. Leukemia 21, 1763–1772 (2007). 175. Koptyra, M., Gupta, S., Talati, P. & Nevalainen, M. T. Signal transducer and activator of transcription 5a/b: Biomarker and therapeutic target in prostate and . International Journal of Biochemistry and Cell Biology 43, 1417– 1421 (2011). 176. Cumaraswamy, A. A., Todic, A., Resetca, D., Minden, M. D. & Gunning, P. T. Inhibitors of Stat5 protein signalling. in MedChemComm 3, 22–27 (2012). 177. Mandal, M. et al. Epigenetic repression of the Igk locus by STAT5-mediated recruitment of the histone methyltransferase Ezh2. Nat. Immunol. 12, 1212–1220 (2011). 178. Grimley, P. M., Dong, F. & Rui, H. Stat5a and Stat5b: Fraternal twins of signal transduction and transcriptional activation. Cytokine and Growth Factor Reviews 10, 131–157 (1999). 179. Nosaka, T. et al. STAT5 as a molecular regulator of proliferation, differentiation and apoptosis in hematopoietic cells. EMBO J. 18, 4754–4765 (1999). 180. Shuai, K., Halpern, J., tenHoeve, J., Rao, X. P. & Sawyers, C. L. Constitutive activation of STAT5 by the BCR-ABL oncogene in chronic myelogenous leukemia. Oncogene 13, 247–254 ST–Constitutive activation of STAT5 by (1996). 181. Cargnello M. et al. Activation and function of the MAPKs and their substrates, the MAPK-activated protein kinases. Microbiol Mol Biol Rev 75, 50-83 (2011).

182. Zhang, W. et al. MAPK signal pathways in the regulation of cell proliferation in mammalian cells. Cell Research 12, 9-18 (2002). 183. Johnson, G. et al. Mitogen-activated protein kinase pathways mediate by ERK, JNK, and p38 protein kinases. Science, 298 (2002). 184. Fey, D. et al. Crosstalk and signaling switched in mitogen-activated protein kinases cascades. Frontiers in Physiology 3, 1-21 (2012).

141

185. Cuevas BD, Abell AN, Johnson GL. Role of mitogen-activated protein kinase kinase kinases in signal integration. Oncogene 26, 3159–3171(2007).

186. Seger, R. et al. The MAPK signaling cascade. FASEB J. 9, 726-735 (1995). 187. Zhang Y, Dong C. Regulatory mechanisms of mitogen-activated kinase signaling. Cell Mol Life Sci 64, 2771–2789 (2007). 188. Raman M, Chen W, Cobb MH. Differential regulation and properties of MAPKs. Oncogene 26, 3100–3112 (2007). 189. Altomare DA, Testa JR. Perturbations of the AKT signaling pathway in human cancer. Oncogene 24, 7455–7464 (2005). 190. Brazil DP, Hemmings BA. Ten years of protein kinase B signalling: A hard Akt to follow. Trends Biochem Sci 26, 657–664 (2001). 191. Alessi DR, James SR, Downes CP, Holmes AB, Gaffney PR, Reese CB, Cohen P. Characterization of a 3-phosphoinositide-dependent protein kinase which phosphorylates and activates protein kinase Bα. Curr Biol 7, 261–269 (1997) 192. Stambolic V, Suzuki A, de la Pompa JL, Brothers GM, Mirtsos C, Sasaki T, Ruland J, Penninger JM, Siderovski DP, Mak TW. Negative regulation of PKB/Akt-dependent cell survival by the tumor suppressor PTEN. Cell 95, 29–39 (1998) 193. Vivanco I, Sawyers CL. The phosphatidylinositol 3-Kinase AKT pathway in human cancer. Nat Rev Cancer 2, 489–501 (2002) 194. Datta SR, Brunet A, Greenberg ME. Cellular survival: A play in three Akts. Genes Dev 13, 2905–2927 (1999). 195. Price P. Standard definitions of terms relating to mass spectrometry : A report from the committee on measurements and standards of the American society for mass spectrometry. Journal of the American Society for Mass Spectrometry 2, 336–48 (1991). 196. Siri, William. Mass spectroscope for analysis in the low-mass range. Review of Scientific Instruments 18, 540–545 (1947). 197. Tanaka K, Waki H, Ido Y, Akita S, Yoshida Y, Yoshida T. Protein and Polymer Analyses up to m/z 100 000 by Laser Ionization Time-of flight Mass Spectrometry. Rapid Commun Mass Spectrom 2, 151–3 (1988). 198. Guilhaus, Michae. Principles and Instrumentation in Time-of-flight Mass Spectrometry. Journal of Mass Spectrometry 30, 1519–1532 (1998). 199. Watson JT, Sparkman OD. Introduction to Mass Spectrometry: Instrumentatio, Applications, and Strategies for Data Interpretation (4th ed.). (2007). 200. Boyd, Robert K. Linked-scan techniques for MS/MS using tandem-in-space instruments. Mass Spectrometry Reviews 13, 359–410 (1994). 201. Fenn JB, Mann M, Meng CK, Wong SF, Whitehouse CM. Electrospray ionization for mass spectrometry of large biomolecules. Science 246, 64–71 (1989).

142

202. Loo JA, Udseth HR, Smith RD. Peptide and protein analysis by electrospray ionization-mass spectrometry and capillary electrophoresis-mass spectrometry. Analytical Biochemistry 179, 404–12 (1989). 203. Pappin DJ, Hojrup P, Bleasby AJ. Rapid identification of proteins by peptide-mass fingerprinting. Curr. Biol 3, 327–32 (1993). 204. Mann M, Højrup P, Roepstorff P. Use of mass spectrometric molecular weight information to identify proteins in sequence databases. Biol. Mass Spectrom. 22, 338–45 (1993).

205. Doerr, Allison. DIA mass spectrometry. Nature Methods 12, 35–35 (2014). 206. Chapman, John D., Goodlett, David R., Masselon, Christophe D. Multiplexed and data-independent tandem mass spectrometry for global proteome profiling. Mass Spectrometry Reviews 33, 452–470 (2014). 207. Bantscheff, M., Schirle, M., Sweetman, G. et al. Quantitative mass spectrometry in proteomics: a critical review. Anal Bioanal Chem 389, 1017 (2007). 208. Zieske LR. A perspective on the use of iTRAQ reagent technology for protein complex and profiling studies. J. Exp. Bot 57, 1501–8. (2006). 209. Gafken PR, Lampe PD. Methodologies for characterizing phosphoproteins by mass spectrometry. Cell Commun. Adhes 13, 249–62 (2006). 210. Shadforth IP, Dunnley PJ, Lilley KS, Bessant C. i-Tracker: For quantitative proteomics using iTRAQ. BMC Genomics 6, 145 (2005). 211. Venable JD, Dong MQ, Wohlschlegel J, Dillin A, Yates JR. Automated approach for quantitative analysis of complex peptide mixtures from tandem mass spectra. Nat. Methods 1, 39–45 (2004). 212. Gillet LC, Navarro P, Tate S, Röst H, Selevsek N, Reiter L, Bonner R, Aebersold R. Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: a new concept for consistent and accurate proteome analysis. Mol. Cell. Proteomics 11 (2012). 213. Russell MR, Walker MJ, Williamson AJ, et al. Protein Z: A putative novel biomarker for early detection of . Int J Cancer.138, 2984-2992. (2016) 214. Szklarczyk, D. et al. The STRING database in 2017: Quality-controlled protein- protein association networks, made broadly accessible. Nucleic Acids Res. 45, D362–D368 (2017) 215. Huang, D. W., Sherman, B. T. & Lempicki, R. A. Bioinformatics enrichment tools: Paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res. 37, 1–13 (2009).

216. Haw R., Hermjakob H., D’Eustachio P., Stein L. Reactome Pathway Analysis to Enrich Biological Discovery in Proteomics Datasets. Proteomics. 11, 3598–3613 (2011).

143

217. Bradford M. A rapid and sensitive method for the quantification of microgram quantities of protein utilizing the principle of protein-dye binding. Analytical chemistry 72, 248-254 (1976). 218. Zheng R. et al. FLT3 ligand causes autocrine signaling in acute myeloid leukemia cells. Blood. 103, 267-74 (2004) 219. Mark Levis, Alexander E. Perl . Gilteritinib: potent targeting of FLT3 mutations in AML. Blood Adv 4, 1178–1191 (2020)

220. Larrosa-Garcia M, Baer MR. FLT3 Inhibitors in Acute Myeloid Leukemia: Current Status and Future Directions. Mol Cancer Ther. 16, 991-1001 (2017)

221. Pratz K, Cherry M, Altman JK, et al. Preliminary results from a phase 1 study of gilteritinib in combination with induction and consolidation chemotherapy in subjects with newly diagnosed acute myeloid leukemia (AML). Blood. 130, abstract 722 (2017) 222. Casado, P., Wilkes, E.H., Miraki-Moud, F. et al. Proteomic and genomic integration identifies kinase and differentiation determinants of kinase inhibitor sensitivity in leukemia cells. Leukemia 32, 1818–1822 (2018). 223. Roolf C, Dybowski N, Sekora A, et al. Phosphoproteome Analysis Reveals Differential Mode of Action of Sorafenib in Wildtype and Mutated FLT3 Acute Myeloid Leukemia (AML) Cells. Mol Cell Proteomics. 16, 1365-1376 (2017) 224. Alcolea MP, Casado P, Rodríguez-Prados JC, Vanhaesebroeck B, Cutillas PR. Phosphoproteomic analysis of leukemia cells under basal and drug-treated conditions identifies markers of kinase pathway activation and mechanisms of resistance. Mol Cell Proteomics.11, 453-66 (2012) 225. Perez M, Blankenhorn J, Murray KJ, Parker LL. High-throughput Identification of FLT3 Wild-type and Mutant Kinase Substrate Preferences and Application to Design of Sensitive In Vitro Kinase Assay Substrates. Mol Cell Proteomics 18, 477-489 (2019) 226. Gu TL, Nardone J, Wang Y, et al. Survey of activated FLT3 signaling in leukemia. PLoS One.6:e19169 (2011) 227. Mali RS, Zhang Q, DeFilippis RA et al. combines synergistically with FLT3 inhibition to effectively target leukemic cells in FLT3-ITD+ acute myeloid leukemia models. Haematologica 244020 (2020) 228. Ma J, Zhao S, Qiao X, Knight T et al. Inhibition of Bcl-2 Synergistically Enhances the Antileukemic Activity of Midostaurin and Gilteritinib in Preclinical Models of FLT3-Mutated Acute Myeloid Leukemia. Clin Cancer Res. 25, 6815-6826 (2019) 229. Quentmeier, H., Reinhardt, J., Zaborski, M. et al. FLT3 mutations in acute myeloid leukemia cell lines. Leukemia 17, 120–124 (2003). 230. Gonneaud, A., Jones, C., Turgeon, N. et al. A SILAC-Based Method for Quantitative Proteomic Analysis of Intestinal Organoids. Sci Rep 6, 38195 (2016).

144

231. Wang, X., He, Y., Ye, Y. et al. SILAC–based quantitative MS approach for real- time recording protein-mediated cell-cell interactions. Sci Rep 8, 8441 (2018). 232. Itzhak DN, Sacco F, Nagaraj N, et al. SILAC-based quantitative proteomics using mass spectrometry quantifies endoplasmic reticulum stress in whole HeLa cells. Dis Model Mech.12 (2019)

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APPENDIX 1 - OVERVIEW OF CURRENTLY AVAILABLE ACUTE MYELOID LEUKAEMIA (AML) HUMAN CELL LINES AND THEIR CHARACTERISTICS.

Cell line Condition FAB Source Cytogenetics Molecular genetics name type classification AML-193 AML M5 - - - AP-1060 APML M3 BM t(15;17) PML/RARα CMK AML M7 PB Complex - EOL-1 AML M4Eos PB del(4) FIP1L1-PDGFRA F-36P AML M6 PE Complex - FKH-1 AML M4 PB T(6;9) DEK-CAN GDM-1 AML M4 PB Complex MNX1 GF-D8 AML M1 PB Complex - HEL AML M6 PB 5q- and 20q- JAK2 V617F HL-60 AML M2 PB Complex c-MYC HNT-34 AML M4 PB t(3;3), t(9;22) MECOM (EVI1), BCR- ABL1 HT-93 AML M3 PB t(15;17) PML/RARα KASUMI-1 AML M2 PB t(8;21) AML1-ETO KASUMI-3 AML M0 BM T(3;7) MECOM-TRB KG-1 AML M6 BM Complex FGFR1OP2-FGFR1 M-07e AML M7 PB Complex - ME-1 AML M4Eos PB inv(16) CBFB-MYH11 MEGAL AML M7 - complex SET-NUP214 MK-PL1 AML M7 BM complex RUNX1 ML-2 AML M4 PB t(6;11) KMT2A-AFDN MOLM-13 AML M5a PB - FLT3/ITD MOLM-14 AML M5a PB complex FLT3/ITD MOLM-16 AML M0 PB complex - MONO-MAC- AML M5 PB t(9;11) KMT2A-MLLT3 1 MUTZ-2 AML M2 PB +8 - MUTZ-3 AML M4 PB t(12;22) - MV4-11 AML M5 - t(4;11) FLT3/ITD NB-4 APML M3 BM t(15;17) PML/RARα NOMO-1 AML M5a BM t(9;11) KMT2A-MLLT3 OCI-AML1 AML M4 PB - - OCI-AML2 AML M4 PB complex DNMT3A R635W OCI AML-3 AML M4 PB der(1)t(1;18) NPM1 OCI-AML4 AML M4 PB complex MLL-ENL OCI-AML5 AML M4 PB - - OCI-AML6 2° AML M4 PB t(3;11) Rearrang MECOM OCI-M1 AML M6 - - - PL-21 APML M3 PB No t(15;17) FLT3/ITD PLB-985 Subclone HL- - - - - 60 SH-2 AML M2 BM - TP53 alteration SIG-M5 AML M5a BM - - SKM-1 AML M5 PB complex - SKNO-1 AML M2 BM t(8;21) AML1-ETO THP-1 AML M5b PB t(9;11) KMT2A-MLLT3 UCSD-AML1 AML - BM t(3;3) and t(12;22) ETV6-MN1 (TEL-MN1) UOC-M1 AML M1 BM - KMT2A (MLL) increase UT-7 AML M7 BM complex - YNH-1 AML M1 PB t(16;21) FUS-ERG (TLS-ERG)

146

APPENDIX 2 - LIST OF THE TOTALITY OF PROTEINS IDENTIFIED FROM THE GENERATED PROTEOMIC DATA, UTILISING THE STRING TOOL.

147

148

149

150

151

APPENDIX 3 - CHANGES IN PROTEIN EXPRESSION IN OCI-AML3 AND MV4-11 CELL LINES. SWATH-MS ANALYSIS RAW DATASETS

Gorcea-Carson, Claudia (2020), “Changes in Protein Expression in OCI-AML3 and MV4-11 cell lines. SWATH-MS analysis raw datasets”, Mendeley Data, V2, doi: 10.17632/4fgzvxpkvv.2 http://dx.doi.org/10.17632/4fgzvxpkvv.2

152

APPENDIX 4 - LIST OF PROTEIN IDENTITIES FROM APOPTOSIS PATHWAY DOWNREGULATED BY THE COMBINATION OF QUIZARTINIB AND FL IN MV4-11 CELL LINE

‘Q07021’ C1QBP - Complement component 1 Q subcomponent-binding protein, mitochondrial; Is believed to be a multifunctional and multicompartmental protein involved in inflammation and infection processes, ribosome biogenesis, regulation of apoptosis, transcriptional regulation and pre-mRNA splicing. At the cell surface is thought to act as an endothelial receptor for plasma proteins of the complement and kallikrein-kinin cascades. Putative receptor for C1q; specifically binds to the globular "heads" of C1q thus inhibiting C1; may perform the receptor function through a complex with C1qR/CD93. In complex [...] [a.k.a. GC1QBP, HABP1, SF2P32, Q07021]

'P10415': BCL2 - Apoptosis regulator Bcl-2; Suppresses apoptosis in a variety of cell systems including factor-dependent lymphohematopoietic and neural cells. Regulates cell death by controlling the mitochondrial membrane permeability. Appears to function in a feedback loop system with caspases. Inhibits caspase activity either by preventing the release of cytochrome c from the mitochondria and/or by binding to the apoptosis-activating factor (APAF-1). May attenuate inflammation by impairing NLRP1-inflammasome activation, hence CASP1 activation and IL1B release; BCL2 family [a.k.a. NP_000624, CAA29778.1, NM_000633, P10415]

'P49720': PSMB3 - Proteasome subunit beta type-3; Component of the 20S core proteasome complex involved in the proteolytic degradation of most intracellular proteins. This complex plays numerous essential roles within the cell by associating with different regulatory particles. Associated with two 19S regulatory particles, forms the 26S proteasome and thus participates in the ATP-dependent degradation of ubiquitinated proteins. The 26S proteasome plays a key role in the maintenance of protein homeostasis by removing misfolded or damaged proteins that could impair cellular functions, and by removing prot [...] [a.k.a. NP_002786.2, uc032glv.2, 5A0Q, P49720]

'Q05397': PTK2 - kinase 1; Non-receptor protein-tyrosine kinase that plays an essential role in regulating cell migration, adhesion, spreading, reorganization of the actin cytoskeleton, formation and disassembly of focal adhesions and cell protrusions, cell cycle progression, cell proliferation and apoptosis. Required for early embryonic development and placenta development. Required for embryonic angiogenesis, normal cardiomyocyte migration and proliferation, and normal heart development. Regulates axon growth and neuronal cell migration, axon branching and synapse formation; required f [...] [a.k.a. FAK1, FAK, PTK2-033, Q05397]

153

'Q13464': ROCK1 - Rho-associated protein kinase 1; Protein kinase which is a key regulator of actin cytoskeleton and cell polarity. Involved in regulation of smooth muscle contraction, actin cytoskeleton organization, stress fiber and focal adhesion formation, neurite retraction, cell adhesion and motility via phosphorylation of DAPK3, GFAP, LIMK1, LIMK2, MYL9/MLC2, PFN1 and PPP1R12A. Phosphorylates FHOD1 and acts synergistically with it to promote SRC- dependent non-apoptotic plasma membrane blebbing. Phosphorylates JIP3 and regulates the recruitment of JNK to JIP3 upon UVB-induced stress. Acts as a sup [...] [a.k.a. 3O0Z, p160ROCK, EF445027, Q13464]

'P25445': FAS - Tumor necrosis factor receptor superfamily member 6; Receptor for TNFSF6/FASLG. The adapter molecule FADD recruits caspase-8 to the activated receptor. The resulting death- inducing signaling complex (DISC) performs caspase-8 proteolytic activation which initiates the subsequent cascade of caspases (aspartate-specific cysteine proteases) mediating apoptosis. FAS- mediated apoptosis may have a role in the induction of peripheral tolerance, in the antigen-stimulated suicide of mature T-cells, or both. The secreted isoforms 2 to 6 block apoptosis (in vitro); CD molecules [a.k.a. TNFRSF6, FAS1, APT1, P25445]

'P49354': FNTA - Protein farnesyltransferase/geranylgeranyltransferase type-1 subunit alpha; Essential subunit of both the farnesyltransferase and the geranylgeranyltransferase complex. Contributes to the transfer of a farnesyl or geranylgeranyl moiety from farnesyl or geranylgeranyl diphosphate to a cysteine at the fourth position from the C-terminus of several proteins having the C-terminal sequence Cys-aliphatic-aliphatic-X. May positively regulate neuromuscular junction development downstream of MUSK via its function in RAC1 prenylation and activation [a.k.a. ENSG00000168522, ENST00000527153, E9PK84, P49354]

'P17980': PSMC3 - 26S proteasome regulatory subunit 6A; Component of the 26S proteasome, a multiprotein complex involved in the ATP-dependent degradation of ubiquitinated proteins. This complex plays a key role in the maintenance of protein homeostasis by removing misfolded or damaged proteins, which could impair cellular functions, and by removing proteins whose functions are no longer required. Therefore, the proteasome participates in numerous cellular processes, including cell cycle progression, apoptosis, or DNA damage repair. PSMC3 belongs to the heterohexameric ring of AAA (ATPases associated wit [...] [a.k.a. TBP1, Tat-binding protein 1, OTTHUMP00000236495, P17980]

'P62195': PSMC5 - 26S proteasome regulatory subunit 8; Component of the 26S proteasome, a multiprotein complex involved in the ATP-dependent degradation of ubiquitinated proteins. This complex plays a key role in the maintenance of protein homeostasis by removing misfolded or damaged proteins, which could impair cellular functions, and by removing proteins whose functions are no longer required. Therefore, the proteasome participates in numerous cellular processes, including cell cycle progression, apoptosis, or DNA damage repair. PSMC5 belongs to the heterohexameric ring of AAA (ATPases associated with [...] [a.k.a. SUG1, AAC41735.1, ENST00000579031, P62195]

154

'P09429': HMGB1 - High mobility group protein B1; Multifunctional redox sensitive protein with various roles in different cellular compartments. In the nucleus is one of the major chromatin- associated non-histone proteins and acts as a DNA chaperone involved in replication, transcription, chromatin remodeling, V(D)J recombination, DNA repair and genome stability. Proposed to be an universal biosensor for nucleic acids. Promotes host inflammatory response to sterile and infectious signals and is involved in the coordination and integration of innate and adaptive immune responses. In the cytoplasm functio [...] [a.k.a. HMG1, ENSP00000406375, XM_005266363.1, P09429]

'P62979': RPS27A - -40S ribosomal protein S27a; Ubiquitin: Exists either covalently attached to another protein, or free (unanchored). When covalently bound, it is conjugated to target proteins via an isopeptide bond either as a monomer (monoubiquitin), a polymer linked via different Lys residues of the ubiquitin (polyubiquitin chains) or a linear polymer linked via the initiator Met of the ubiquitin (linear polyubiquitin chains). Polyubiquitin chains, when attached to a target protein, have different functions depending on the Lys residue of the ubiquitin that is linked: Lys- 6-linked may be inv [...] [a.k.a. UBA80, UBCEP1, 4V6X, P62979]

155

APPENDIX 5 - LIST OF PROTEIN IDENTITIES FROM THE CELL CYCLE PATHWAY UPREGULATED BY THE COMBINATION OF QUIZARTINIB AND FL IN MV4-11 CELL LINE

‘Q07021’: C1QBP - Complement component 1 Q subcomponent-binding protein, mitochondrial; Is believed to be a multifunctional and multicompartmental protein involved in inflammation and infection processes, ribosome biogenesis, regulation of apoptosis, transcriptional regulation and pre-mRNA splicing. At the cell surface is thought to act as an endothelial receptor for plasma proteins of the complement and kallikrein-kinin cascades. Putative receptor for C1q; specifically binds to the globular "heads" of C1q thus inhibiting C1; may perform the receptor function through a complex with C1qR/CD93. In complex [...] [a.k.a. GC1QBP, HABP1, SF2P32, Q07021]

'P10415': BCL2 - Apoptosis regulator Bcl-2; Suppresses apoptosis in a variety of cell systems including factor-dependent lymphohematopoietic and neural cells. Regulates cell death by controlling the mitochondrial membrane permeability. Appears to function in a feedback loop system with caspases. Inhibits caspase activity either by preventing the release of cytochrome c from the mitochondria and/or by binding to the apoptosis-activating factor (APAF-1). May attenuate inflammation by impairing NLRP1-inflammasome activation, hence CASP1 activation and IL1B release; BCL2 family [a.k.a. NP_000624, CAA29778.1, NM_000633, P10415]

'P49720': PSMB3 - Proteasome subunit beta type-3; Component of the 20S core proteasome complex involved in the proteolytic degradation of most intracellular proteins. This complex plays numerous essential roles within the cell by associating with different regulatory particles. Associated with two 19S regulatory particles, forms the 26S proteasome and thus participates in the ATP-dependent degradation of ubiquitinated proteins. The 26S proteasome plays a key role in the maintenance of protein homeostasis by removing misfolded or damaged proteins that could impair cellular functions, and by removing prot [...] [a.k.a. NP_002786.2, uc032glv.2, 5A0Q, P49720]

'Q05397': PTK2 - Focal adhesion kinase 1; Non-receptor protein-tyrosine kinase that plays an essential role in regulating cell migration, adhesion, spreading, reorganization of the actin cytoskeleton, formation and disassembly of focal adhesions and cell protrusions, cell cycle progression, cell proliferation and apoptosis. Required for early embryonic development and placenta development. Required for embryonic angiogenesis, normal cardiomyocyte migration and proliferation, and normal heart development. Regulates axon growth and neuronal cell migration, axon branching and synapse formation; required f [...] [a.k.a. FAK1, FAK, PTK2-033, Q05397]

156

'Q13464': ROCK1 - Rho-associated protein kinase 1; Protein kinase which is a key regulator of actin cytoskeleton and cell polarity. Involved in regulation of smooth muscle contraction, actin cytoskeleton organization, stress fiber and focal adhesion formation, neurite retraction, cell adhesion and motility via phosphorylation of DAPK3, GFAP, LIMK1, LIMK2, MYL9/MLC2, PFN1 and PPP1R12A. Phosphorylates FHOD1 and acts synergistically with it to promote SRC- dependent non-apoptotic plasma membrane blebbing. Phosphorylates JIP3 and regulates the recruitment of JNK to JIP3 upon UVB-induced stress. Acts as a sup [...] [a.k.a. 3O0Z, p160ROCK, EF445027, Q13464]

'P25445': FAS - Tumor necrosis factor receptor superfamily member 6; Receptor for TNFSF6/FASLG. The adapter molecule FADD recruits caspase-8 to the activated receptor. The resulting death- inducing signaling complex (DISC) performs caspase-8 proteolytic activation which initiates the subsequent cascade of caspases (aspartate-specific cysteine proteases) mediating apoptosis. FAS- mediated apoptosis may have a role in the induction of peripheral tolerance, in the antigen-stimulated suicide of mature T-cells, or both. The secreted isoforms 2 to 6 block apoptosis (in vitro); CD molecules [a.k.a. TNFRSF6, FAS1, APT1, P25445]

'P49354': FNTA - Protein farnesyltransferase/geranylgeranyltransferase type-1 subunit alpha; Essential subunit of both the farnesyltransferase and the geranylgeranyltransferase complex. Contributes to the transfer of a farnesyl or geranylgeranyl moiety from farnesyl or geranylgeranyl diphosphate to a cysteine at the fourth position from the C-terminus of several proteins having the C-terminal sequence Cys-aliphatic-aliphatic-X. May positively regulate neuromuscular junction development downstream of MUSK via its function in RAC1 prenylation and activation [a.k.a. ENSG00000168522, ENST00000527153, E9PK84, P49354]

'P17980': PSMC3 - 26S proteasome regulatory subunit 6A; Component of the 26S proteasome, a multiprotein complex involved in the ATP-dependent degradation of ubiquitinated proteins. This complex plays a key role in the maintenance of protein homeostasis by removing misfolded or damaged proteins, which could impair cellular functions, and by removing proteins whose functions are no longer required. Therefore, the proteasome participates in numerous cellular processes, including cell cycle progression, apoptosis, or DNA damage repair. PSMC3 belongs to the heterohexameric ring of AAA (ATPases associated wit [...] [a.k.a. TBP1, Tat-binding protein 1, OTTHUMP00000236495, P17980]

'P62195': PSMC5 - 26S proteasome regulatory subunit 8; Component of the 26S proteasome, a multiprotein complex involved in the ATP-dependent degradation of ubiquitinated proteins. This complex plays a key role in the maintenance of protein homeostasis by removing misfolded or damaged proteins, which could impair cellular functions, and by removing proteins whose functions are no longer required. Therefore, the proteasome participates in numerous cellular processes, including cell cycle progression, apoptosis, or DNA damage repair. PSMC5 belongs to the heterohexameric ring of AAA (ATPases associated with [...] [a.k.a. SUG1, AAC41735.1, ENST00000579031, P62195]

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'P09429': HMGB1 - High mobility group protein B1; Multifunctional redox sensitive protein with various roles in different cellular compartments. In the nucleus is one of the major chromatin- associated non-histone proteins and acts as a DNA chaperone involved in replication, transcription, chromatin remodeling, V(D)J recombination, DNA repair and genome stability. Proposed to be an universal biosensor for nucleic acids. Promotes host inflammatory response to sterile and infectious signals and is involved in the coordination and integration of innate and adaptive immune responses. In the cytoplasm functio [...] [a.k.a. HMG1, ENSP00000406375, XM_005266363.1, P09429]

'P62979': RPS27A - Ubiquitin-40S ribosomal protein S27a; Ubiquitin: Exists either covalently attached to another protein, or free (unanchored). When covalently bound, it is conjugated to target proteins via an isopeptide bond either as a monomer (monoubiquitin), a polymer linked via different Lys residues of the ubiquitin (polyubiquitin chains) or a linear polymer linked via the initiator Met of the ubiquitin (linear polyubiquitin chains). Polyubiquitin chains, when attached to a target protein, have different functions depending on the Lys residue of the ubiquitin that is linked: Lys- 6-linked may be inv [...] [a.k.a. UBA80, UBCEP1, 4V6X, P62979]

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